The time-varying demands for a certain period are often assumed to be less than the basic economic order quantity （EOQ） so that total replenishment quantity rather than economic order quantity is normally considered...The time-varying demands for a certain period are often assumed to be less than the basic economic order quantity （EOQ） so that total replenishment quantity rather than economic order quantity is normally considered by most of the heuristics. This acticle focuses on a combined heuristics method for determining order quantity under generalized time-varying demands. The independent policy （IP）, abnormal independent policy （AIP） and dependent policies are studied and compared. Using the concepts of normal/abnormal periods and the properties of dependent policies, a dependent policy-based heuristics （DPH） is proposed for solving the order quantity problems with a kind of time-varying demands pattern under which the first period is normal. By merging the Silver-Meal （S-M） heuristics and the dependent policy-based heuristics （DPH）, a combined heuristics （DPH/S-M） is developed for solving order quantity problems with generalized time-varying demands. The experimentation shows that （1） for the problem with one normal period, no matter which position the normal period stands, the DPH/S-M could not guarantee better than the S-M heuristics, however it is superior to the S-M heuristics in the case that the demands in the abnormal periods are in descending order, and （2） The DPH/S-M is superior to the S-M heuristics for problems with more than one normal period, and the more the number of normal periods, the greater the improvements.展开更多
This paper discusses an optimization of operating a p ermutation circulation-type vehicle routing system (PCVRS, for short), in w hich several stages are located along by a single loop, and a fleet of vehicles travels...This paper discusses an optimization of operating a p ermutation circulation-type vehicle routing system (PCVRS, for short), in w hich several stages are located along by a single loop, and a fleet of vehicles travels on the loop unidirectionally and repeatedly. Traveling on the loop, each vehicle receives an object from the loading stage and then carries it to a cert ain processing stage, or receives an object from a certain processing stage and then carries it to the unloading stage per a turnaround. No passing is allowed f or the vehicles on the loop (from which the system is called permutation, and th is restriction may cause interferences between vehicles). Material handling systems such as PCVRS are actually encountered in flexible man ufacturing systems and in automated storage/retrieval systems. In this paper, we propose a heuristic algorithm for operating the PCVRS, which i ncorporates a new scheduling method for the vehicles with the SPT (shortest proc essing time) numbering of jobs and a round-robin manner of allocating jobs to t he stages, aiming to reduce interferences between the vehicles. We also give num erical results with respect to system performances attained by the heuristic. Description of the system The PCVRS consists of a set of n v vehicles V={V 1,V 2,...,V n v}, a set of n s, processing stages S p={S 1,S 2,...,S n s}, a loading stage S 0 and an unloading stage S n s +1. We denote by S=S p∪{S 0,S n s+l} the set of all the stages. The vehicles travel on a single loop unidirectionany and repeated ly. The system layout is depicted in Fig.1. There is a set of n jobs J={J 1,J 2,...,J n} to be processed b y the vehicles. Each job consists of two tasks: That is, each vehicle receives a n object from S 0 and then carries it to S l with a certain l∈{1,2, ...,n s} (a throw-in job), or receives an object from S l with a certain l∈{1,2,...,n s} and then carries it to S n s+1 (a throw-out job ) per a turnaround. The loop consists of buffer zones BZ(l) and travel zones TZ(l) (see Fig. 1). Each buffer zone BZ(l) is placed in front of stage S l, l=0,1,..., n s, n s+1, in order to avoid a collision between vehicles (i.e., the syste m adopts the so-called zone control strategy). A heuristic algorithm We develop a heuristic algorithm to obtain a good performance for the PCVRS. An operation π={A/B/C} for the PCVRS consists of three decision factors: (A) Numbering jobs Jobs are loaded into S 0 according to an assending order of job numbers. In this paper, we use the following rules to number jobs: SPT: Order jobs in the shortest processing time rule, i.e., P 1≤P 2≤...≤P n for the set of jobs J={J 1,J 2,...,J n}, rather than the FCFS numbering (i.e., number jobs in first-come-first-served order). The SPT rule intends to reduce interferences between two adjacent vehicles at stages. (B) Allocating jobs to stages For the purpose of balancing loads of processing stages, we adopt the following to allocate jobs to the stages: ORDER: Allocate n jobs to n s, processing stages by an in-order manner , i.e., let l(i) be the index of processing stage allocated job J i by ORDER, it holds that l(i)=n s+1-(i-[(i-1)/n s]n s).(1) The ORDER rule intends to process jobs parallel at stages as many as possible. (C) Scheduling vehicles The following method for scheduling vehicles under ORDER rule is already known: Fig.1 The vehicle ro uting system, PCVRS Fig.2 Mean turnaroun d times by heuristics Unchange: Assign n jobs to n v vehicles such that let k(i) be the i ndex of vehicle processing job J i, then k(i)= i-[(i-1)/n v]n v.(2) In csse of n v≥n s, mod (n v,n s)=0 or n v<n s, mod (n s,n v)=0 (mod(x,y) is the remainder of x/y), the number of interferences between vehicles is minimized at stage S 1 under Unchange sche dules, while in the other cases it is not [Lu et al. (2001a)]. Therefore, in t his paper, we develop a new scheduling method of the vehicles, denoted by Ex change, to modify Unchange schedules. Note展开更多
The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of s...The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.展开更多
As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in mult...As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.展开更多
As battlefield scale enlarges,cross-platform collaborative combat provides an appealing paradigm for modern warfare.Complicated constraints and vast solution space pose great challenge for reasonable and efficient mis...As battlefield scale enlarges,cross-platform collaborative combat provides an appealing paradigm for modern warfare.Complicated constraints and vast solution space pose great challenge for reasonable and efficient mission planning,where path planning and target assignment are tightly coupled.In this paper,we focus on UAV mission planning under carrier delivery mode(e.g.,by aircraft carrier,ground vehicle,or transport aircraft) and design a three-layer hierarchical solution framework.In the first layer,we simultaneously determine delivery points and target set division by clustering.To address the safety concerns of radar risk and UAV endurance,an improved density peak clustering algorithm is developed by constraint fusio n.In the second layer,mission planning within each cluster is viewed as a coope rative multiple-task assignment problem.A hybrid heuristic algorithm that integrates a voting-based heuristic solution generation strategy(VHSG) and a stochastic variable neighborhood search(SVNS),called VHSG-SVNS,is proposed for rapid solution.Based on the results of the first two layers,the third layer transforms carrier path planning into a multiple-vehicle routing problem with time window.The cost between any two nodes is calculated by the A~* algorithm,and the genetic algorithm is then implemented to determine the global route.Finally,a practical mission scenario containing 200 targets is used to validate the effectiveness of the designed framework,where three layers cooperate well with each other to generate satisfactory combat scheduling.Comparisons are made in each layer to highlight optimum-seeking capability and efficiency of the proposed algorithms.Works done in this paper provide a simple but efficient solution framework for cross-platform cooperative mission planning problems,and can be potentially extended to other applications such as post-disaster search and rescue,forest surveillance and firefighting,logistics pick and delivery,etc.展开更多
To deal with the radio frequency threat posed by modern complex radar networks to aircraft,we researched the unmanned aerial vehicle(UAV)formations radar countermeasures,aiming at the solution of radar jamming resourc...To deal with the radio frequency threat posed by modern complex radar networks to aircraft,we researched the unmanned aerial vehicle(UAV)formations radar countermeasures,aiming at the solution of radar jamming resource allocation under system countermeasures.A jamming resource allocation method based on an improved firefly algorithm(FA)is proposed.Firstly,the comprehensive factors affecting the level of threat and interference efficiency of radiation source are quantified by a fuzzy comprehensive evaluation.Besides,the interference efficiency matrix and the objective function of the allocation model are determined to establish the interference resource allocation model.Finally,A mutation operator and an adaptive heuristic are integtated into the FA algorithm,which searches an interference resource allocation scheme.The simulation results show that the improved FA algorithm can compensate for the deficiencies of the FA algorithm.The improved FA algorithm provides a more scientific and reasonable decision-making plan for aircraft mission allocation and can effectively deal with the battlefield threats of the enemy radar network.Moreover,in terms of convergence accuracy and speed as well as algorithm stability,the improved FA algorithm is superior to the simulated annealing algorithm(SA),the niche genetic algorithm(NGA),the improved discrete cuckoo algorithm(IDCS),the mutant firefly algorithm(MFA),the cuckoo search and fireflies algorithm(CSFA),and the best neighbor firefly algorithm(BNFA).展开更多
This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations amo...This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations among the activities which require some kinds of renewable resources. We predigest the process of sol-ving the resource availability cost problem （RACP） by using start time of each activity to code the schedule. Then, a novel heuris-tic algorithm is proposed to make the process of looking for the best solution efficiently. And then pseudo particle swarm optimiza-tion （PPSO） combined with PSO and path relinking procedure is presented to solve the RACP. Final y, comparative computational experiments are designed and the computational results show that the proposed method is very effective to solve RACP.展开更多
Studies show that supply chain cooperation improves supply chain performance. However, it remains a challenge to develop and implement the realistic supply chain cooperation scheme. We investigate a two-echelon supply...Studies show that supply chain cooperation improves supply chain performance. However, it remains a challenge to develop and implement the realistic supply chain cooperation scheme. We investigate a two-echelon supply chain planning problem with capacity acquisition decision under asymmetric cost and demand information. A simple negotiation-based coordination mechanism is developed to synchronize production/order strategies of a supplier and a buyer. The coordination scheme shows how the supplier and the buyer modify their production and order policy in order to find a joint economic lot sizing plan, which saves the overall supply chain cost. The allocation of the cooperation benefit is determined by negotiation. Due to the complexity of the multiple periods, multiple level supply chain lot sizing with capacity decision, a heuristic algorithm is developed to find coordination solutions. Finally, the results of the numerical study indicate the performance of supply chain coordination scheme.展开更多
Ant colony optimization （ACO） is a new heuristic algo- rithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. The traveling salesman problem （TSP） is amo...Ant colony optimization （ACO） is a new heuristic algo- rithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. The traveling salesman problem （TSP） is among the most important combinato- rial problems. An ACO algorithm based on scout characteristic is proposed for solving the stagnation behavior and premature con- vergence problem of the basic ACO algorithm on TSP. The main idea is to partition artificial ants into two groups： scout ants and common ants. The common ants work according to the search manner of basic ant colony algorithm, but scout ants have some differences from common ants, they calculate each route＇s muta- tion probability of the current optimal solution using path evaluation model and search around the optimal solution according to the mutation probability. Simulation on TSP shows that the improved algorithm has high efficiency and robustness.展开更多
To solve the scheduling problem of dual-armed cluster tools for wafer fabrications with residency time and reentrant constraints,a heuristic scheduling algorithm was developed.Firstly,on the basis of formulating sched...To solve the scheduling problem of dual-armed cluster tools for wafer fabrications with residency time and reentrant constraints,a heuristic scheduling algorithm was developed.Firstly,on the basis of formulating scheduling problems domain of dual-armed cluster tools,a non-integer programming model was set up with a minimizing objective function of the makespan.Combining characteristics of residency time and reentrant constraints,a scheduling algorithm of searching the optimal operation path of dual-armed transport module was presented under many kinds of robotic scheduling paths for dual-armed cluster tools.Finally,the experiments were designed to evaluate the proposed algorithm.The results show that the proposed algorithm is feasible and efficient for obtaining an optimal scheduling solution of dual-armed cluster tools with residency time and reentrant constraints.展开更多
The volatile chemical components of Radix Paeoniae Rubra (RPR) were analyzed by gas chromatography-mass spectrometry with the method of heuristic evolving latent projections and overall volume integration. The results...The volatile chemical components of Radix Paeoniae Rubra (RPR) were analyzed by gas chromatography-mass spectrometry with the method of heuristic evolving latent projections and overall volume integration. The results show that 38 volatile chemical components of RPR are determined, accounting for 95.21% of total contents of volatile chemical components of RPR. The main volatile chemical components of RPR are (Z, Z)-9,12-octadecadienoic acid, n-hexadecanoic acid, 2-hydroxy- benzaldehyde, 1-(2-hydroxy-4-methoxyphenyl)-ethanone, 6,6-dimethyl-bicyclo[3.1.1] heptane-2-methanol, 4,7-dimethyl-benzofuran, 4-(1-methylethenyl)-1-cyclohexene-1-carboxaldehyde, and cyclohexadecane.展开更多
An efficient method for quality control of Fructus Aurantii Immaturus (FAI),a famous traditional Chinese medicine (TCM) was established. A simple and reliable high-performance liquid chromatography-photodiode array de...An efficient method for quality control of Fructus Aurantii Immaturus (FAI),a famous traditional Chinese medicine (TCM) was established. A simple and reliable high-performance liquid chromatography-photodiode array detector (HPLC-DAD) procedure coupled with chemometric methods was developed for fingerprint analysis,qualitative analysis and quantitative determination of this herb. In qualitative and quantitative analyses,heuristic evolving latent projection (HELP) method was employed to resolve the overlapping peaks of the tested samples. Two bioactive components,namely hesperidin and naringin,are confirmed and determined,together with four flavonoids compounds tentatively identified including two new ones. From fingerprint analysis,the fingerprint data were processed with correlation coefficients for quantitative expression of their similarity and dissimilarity. The developed method based on an integration of chromatographic fingerprint and quantitative analysis is scientific,and the obtained results can be applied to the quality control of herb medicine.展开更多
Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the re...Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the project scheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.展开更多
Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the...Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the character and structure of scheduling. An optimal scheduling strategy in collision window is presented. Performance evaluation of this algorithm is given. Simulation indicates that the proposed algorithm is better than other common heuristic algorithms on both the total performance and stability.展开更多
In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic...In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic priority. However,the priority of the imaging task is dynamic in actual engineering. To supplement the research on imaging observation, this paper proposes the task priority model, dynamic scheduling strategy and Heuristic algorithm. At first, this paper analyzes the relevant theoretical basis of imaging observation, decomposes the task priority into four parts, including target priority, imaging task priority, track, telemetry & control(TT&C)requirement priority and data transmission requirement priority, summarizes the attribute factors that affect the above four types of priority in detail, and designs the corresponding priority model. Then, this paper takes the emergency tasks scheduling problem as the background, proposes the dynamic scheduling strategy and heuristic algorithm. Finally, the task priority model,dynamic scheduling strategy and heuristic algorithm are verified by experiments.展开更多
Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the sched...Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the scheduling of EOSs.The proactive-reactive scheduling framework has been proven to be effective and efficient for the uncertain scheduling problem and has been extensively employed.Numerous studies have been conducted on methods for the proactive scheduling of EOSs,including expectation,chance-constrained,and robust optimization models and the relevant solution algorithms.This study focuses on the reactive scheduling of EOSs under cloud uncertainties.First,using an example,we describe the reactive scheduling problem in detail,clarifying its significance and key issues.Considering the two key objectives of observation profits and scheduling stability,we construct a multi-objective optimization mathematical model.Then,we obtain the possible disruptions of EOS scheduling during execution under cloud uncertainties,adopting an event-driven policy for the reactive scheduling.For the different disruptions,different reactive scheduling algorithms are designed.Finally,numerous simulation experiments are conducted to verify the feasibility and effectiveness of the proposed reactive scheduling algorithms.The experimental results show that the reactive scheduling algorithms can both improve observation profits and reduce system perturbations.展开更多
基金the National Natural Science Foundation of China (70625001 70431003+2 种基金 70601004)theKey Project of Scientific and Research of MOE (104064)the Program of New Century Excellent Talents ( NCET-04-0280) ofMOE.
文摘The time-varying demands for a certain period are often assumed to be less than the basic economic order quantity （EOQ） so that total replenishment quantity rather than economic order quantity is normally considered by most of the heuristics. This acticle focuses on a combined heuristics method for determining order quantity under generalized time-varying demands. The independent policy （IP）, abnormal independent policy （AIP） and dependent policies are studied and compared. Using the concepts of normal/abnormal periods and the properties of dependent policies, a dependent policy-based heuristics （DPH） is proposed for solving the order quantity problems with a kind of time-varying demands pattern under which the first period is normal. By merging the Silver-Meal （S-M） heuristics and the dependent policy-based heuristics （DPH）, a combined heuristics （DPH/S-M） is developed for solving order quantity problems with generalized time-varying demands. The experimentation shows that （1） for the problem with one normal period, no matter which position the normal period stands, the DPH/S-M could not guarantee better than the S-M heuristics, however it is superior to the S-M heuristics in the case that the demands in the abnormal periods are in descending order, and （2） The DPH/S-M is superior to the S-M heuristics for problems with more than one normal period, and the more the number of normal periods, the greater the improvements.
文摘This paper discusses an optimization of operating a p ermutation circulation-type vehicle routing system (PCVRS, for short), in w hich several stages are located along by a single loop, and a fleet of vehicles travels on the loop unidirectionally and repeatedly. Traveling on the loop, each vehicle receives an object from the loading stage and then carries it to a cert ain processing stage, or receives an object from a certain processing stage and then carries it to the unloading stage per a turnaround. No passing is allowed f or the vehicles on the loop (from which the system is called permutation, and th is restriction may cause interferences between vehicles). Material handling systems such as PCVRS are actually encountered in flexible man ufacturing systems and in automated storage/retrieval systems. In this paper, we propose a heuristic algorithm for operating the PCVRS, which i ncorporates a new scheduling method for the vehicles with the SPT (shortest proc essing time) numbering of jobs and a round-robin manner of allocating jobs to t he stages, aiming to reduce interferences between the vehicles. We also give num erical results with respect to system performances attained by the heuristic. Description of the system The PCVRS consists of a set of n v vehicles V={V 1,V 2,...,V n v}, a set of n s, processing stages S p={S 1,S 2,...,S n s}, a loading stage S 0 and an unloading stage S n s +1. We denote by S=S p∪{S 0,S n s+l} the set of all the stages. The vehicles travel on a single loop unidirectionany and repeated ly. The system layout is depicted in Fig.1. There is a set of n jobs J={J 1,J 2,...,J n} to be processed b y the vehicles. Each job consists of two tasks: That is, each vehicle receives a n object from S 0 and then carries it to S l with a certain l∈{1,2, ...,n s} (a throw-in job), or receives an object from S l with a certain l∈{1,2,...,n s} and then carries it to S n s+1 (a throw-out job ) per a turnaround. The loop consists of buffer zones BZ(l) and travel zones TZ(l) (see Fig. 1). Each buffer zone BZ(l) is placed in front of stage S l, l=0,1,..., n s, n s+1, in order to avoid a collision between vehicles (i.e., the syste m adopts the so-called zone control strategy). A heuristic algorithm We develop a heuristic algorithm to obtain a good performance for the PCVRS. An operation π={A/B/C} for the PCVRS consists of three decision factors: (A) Numbering jobs Jobs are loaded into S 0 according to an assending order of job numbers. In this paper, we use the following rules to number jobs: SPT: Order jobs in the shortest processing time rule, i.e., P 1≤P 2≤...≤P n for the set of jobs J={J 1,J 2,...,J n}, rather than the FCFS numbering (i.e., number jobs in first-come-first-served order). The SPT rule intends to reduce interferences between two adjacent vehicles at stages. (B) Allocating jobs to stages For the purpose of balancing loads of processing stages, we adopt the following to allocate jobs to the stages: ORDER: Allocate n jobs to n s, processing stages by an in-order manner , i.e., let l(i) be the index of processing stage allocated job J i by ORDER, it holds that l(i)=n s+1-(i-[(i-1)/n s]n s).(1) The ORDER rule intends to process jobs parallel at stages as many as possible. (C) Scheduling vehicles The following method for scheduling vehicles under ORDER rule is already known: Fig.1 The vehicle ro uting system, PCVRS Fig.2 Mean turnaroun d times by heuristics Unchange: Assign n jobs to n v vehicles such that let k(i) be the i ndex of vehicle processing job J i, then k(i)= i-[(i-1)/n v]n v.(2) In csse of n v≥n s, mod (n v,n s)=0 or n v<n s, mod (n s,n v)=0 (mod(x,y) is the remainder of x/y), the number of interferences between vehicles is minimized at stage S 1 under Unchange sche dules, while in the other cases it is not [Lu et al. (2001a)]. Therefore, in t his paper, we develop a new scheduling method of the vehicles, denoted by Ex change, to modify Unchange schedules. Note
文摘The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.
文摘As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.
文摘As battlefield scale enlarges,cross-platform collaborative combat provides an appealing paradigm for modern warfare.Complicated constraints and vast solution space pose great challenge for reasonable and efficient mission planning,where path planning and target assignment are tightly coupled.In this paper,we focus on UAV mission planning under carrier delivery mode(e.g.,by aircraft carrier,ground vehicle,or transport aircraft) and design a three-layer hierarchical solution framework.In the first layer,we simultaneously determine delivery points and target set division by clustering.To address the safety concerns of radar risk and UAV endurance,an improved density peak clustering algorithm is developed by constraint fusio n.In the second layer,mission planning within each cluster is viewed as a coope rative multiple-task assignment problem.A hybrid heuristic algorithm that integrates a voting-based heuristic solution generation strategy(VHSG) and a stochastic variable neighborhood search(SVNS),called VHSG-SVNS,is proposed for rapid solution.Based on the results of the first two layers,the third layer transforms carrier path planning into a multiple-vehicle routing problem with time window.The cost between any two nodes is calculated by the A~* algorithm,and the genetic algorithm is then implemented to determine the global route.Finally,a practical mission scenario containing 200 targets is used to validate the effectiveness of the designed framework,where three layers cooperate well with each other to generate satisfactory combat scheduling.Comparisons are made in each layer to highlight optimum-seeking capability and efficiency of the proposed algorithms.Works done in this paper provide a simple but efficient solution framework for cross-platform cooperative mission planning problems,and can be potentially extended to other applications such as post-disaster search and rescue,forest surveillance and firefighting,logistics pick and delivery,etc.
文摘To deal with the radio frequency threat posed by modern complex radar networks to aircraft,we researched the unmanned aerial vehicle(UAV)formations radar countermeasures,aiming at the solution of radar jamming resource allocation under system countermeasures.A jamming resource allocation method based on an improved firefly algorithm(FA)is proposed.Firstly,the comprehensive factors affecting the level of threat and interference efficiency of radiation source are quantified by a fuzzy comprehensive evaluation.Besides,the interference efficiency matrix and the objective function of the allocation model are determined to establish the interference resource allocation model.Finally,A mutation operator and an adaptive heuristic are integtated into the FA algorithm,which searches an interference resource allocation scheme.The simulation results show that the improved FA algorithm can compensate for the deficiencies of the FA algorithm.The improved FA algorithm provides a more scientific and reasonable decision-making plan for aircraft mission allocation and can effectively deal with the battlefield threats of the enemy radar network.Moreover,in terms of convergence accuracy and speed as well as algorithm stability,the improved FA algorithm is superior to the simulated annealing algorithm(SA),the niche genetic algorithm(NGA),the improved discrete cuckoo algorithm(IDCS),the mutant firefly algorithm(MFA),the cuckoo search and fireflies algorithm(CSFA),and the best neighbor firefly algorithm(BNFA).
基金supported by the National Natural Science Foundation of China(7120116671201170)
文摘This paper considers a project scheduling problem with the objective of minimizing resource availability costs appealed to finish al activities before the deadline. There are finish-start type precedence relations among the activities which require some kinds of renewable resources. We predigest the process of sol-ving the resource availability cost problem （RACP） by using start time of each activity to code the schedule. Then, a novel heuris-tic algorithm is proposed to make the process of looking for the best solution efficiently. And then pseudo particle swarm optimiza-tion （PPSO） combined with PSO and path relinking procedure is presented to solve the RACP. Final y, comparative computational experiments are designed and the computational results show that the proposed method is very effective to solve RACP.
基金supported by the National Natural Science Foundation of China (70701008)
文摘Studies show that supply chain cooperation improves supply chain performance. However, it remains a challenge to develop and implement the realistic supply chain cooperation scheme. We investigate a two-echelon supply chain planning problem with capacity acquisition decision under asymmetric cost and demand information. A simple negotiation-based coordination mechanism is developed to synchronize production/order strategies of a supplier and a buyer. The coordination scheme shows how the supplier and the buyer modify their production and order policy in order to find a joint economic lot sizing plan, which saves the overall supply chain cost. The allocation of the cooperation benefit is determined by negotiation. Due to the complexity of the multiple periods, multiple level supply chain lot sizing with capacity decision, a heuristic algorithm is developed to find coordination solutions. Finally, the results of the numerical study indicate the performance of supply chain coordination scheme.
基金supported by the National Natural Science Foundation of China(60573159)
文摘Ant colony optimization （ACO） is a new heuristic algo- rithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. The traveling salesman problem （TSP） is among the most important combinato- rial problems. An ACO algorithm based on scout characteristic is proposed for solving the stagnation behavior and premature con- vergence problem of the basic ACO algorithm on TSP. The main idea is to partition artificial ants into two groups： scout ants and common ants. The common ants work according to the search manner of basic ant colony algorithm, but scout ants have some differences from common ants, they calculate each route＇s muta- tion probability of the current optimal solution using path evaluation model and search around the optimal solution according to the mutation probability. Simulation on TSP shows that the improved algorithm has high efficiency and robustness.
基金Projects(7107111561273035)supported by the National Natural Science Foundation of China
文摘To solve the scheduling problem of dual-armed cluster tools for wafer fabrications with residency time and reentrant constraints,a heuristic scheduling algorithm was developed.Firstly,on the basis of formulating scheduling problems domain of dual-armed cluster tools,a non-integer programming model was set up with a minimizing objective function of the makespan.Combining characteristics of residency time and reentrant constraints,a scheduling algorithm of searching the optimal operation path of dual-armed transport module was presented under many kinds of robotic scheduling paths for dual-armed cluster tools.Finally,the experiments were designed to evaluate the proposed algorithm.The results show that the proposed algorithm is feasible and efficient for obtaining an optimal scheduling solution of dual-armed cluster tools with residency time and reentrant constraints.
基金Project(20235020) supported by the National Natural Science Foundation of China
文摘The volatile chemical components of Radix Paeoniae Rubra (RPR) were analyzed by gas chromatography-mass spectrometry with the method of heuristic evolving latent projections and overall volume integration. The results show that 38 volatile chemical components of RPR are determined, accounting for 95.21% of total contents of volatile chemical components of RPR. The main volatile chemical components of RPR are (Z, Z)-9,12-octadecadienoic acid, n-hexadecanoic acid, 2-hydroxy- benzaldehyde, 1-(2-hydroxy-4-methoxyphenyl)-ethanone, 6,6-dimethyl-bicyclo[3.1.1] heptane-2-methanol, 4,7-dimethyl-benzofuran, 4-(1-methylethenyl)-1-cyclohexene-1-carboxaldehyde, and cyclohexadecane.
基金Project(20875104) supported by the National Natural Science Foundation of ChinaProject(10SDF22) supported by the Special Foundation of China Postdoctoral ScienceProject(201021200011) supported by the Advanced Research Plan of Central South University, China
文摘An efficient method for quality control of Fructus Aurantii Immaturus (FAI),a famous traditional Chinese medicine (TCM) was established. A simple and reliable high-performance liquid chromatography-photodiode array detector (HPLC-DAD) procedure coupled with chemometric methods was developed for fingerprint analysis,qualitative analysis and quantitative determination of this herb. In qualitative and quantitative analyses,heuristic evolving latent projection (HELP) method was employed to resolve the overlapping peaks of the tested samples. Two bioactive components,namely hesperidin and naringin,are confirmed and determined,together with four flavonoids compounds tentatively identified including two new ones. From fingerprint analysis,the fingerprint data were processed with correlation coefficients for quantitative expression of their similarity and dissimilarity. The developed method based on an integration of chromatographic fingerprint and quantitative analysis is scientific,and the obtained results can be applied to the quality control of herb medicine.
文摘Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the project scheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.
文摘Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the character and structure of scheduling. An optimal scheduling strategy in collision window is presented. Performance evaluation of this algorithm is given. Simulation indicates that the proposed algorithm is better than other common heuristic algorithms on both the total performance and stability.
基金supported by the National Natural Science Foundation of China(61773120,61473301,71501180,71501179,61603400)。
文摘In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic priority. However,the priority of the imaging task is dynamic in actual engineering. To supplement the research on imaging observation, this paper proposes the task priority model, dynamic scheduling strategy and Heuristic algorithm. At first, this paper analyzes the relevant theoretical basis of imaging observation, decomposes the task priority into four parts, including target priority, imaging task priority, track, telemetry & control(TT&C)requirement priority and data transmission requirement priority, summarizes the attribute factors that affect the above four types of priority in detail, and designs the corresponding priority model. Then, this paper takes the emergency tasks scheduling problem as the background, proposes the dynamic scheduling strategy and heuristic algorithm. Finally, the task priority model,dynamic scheduling strategy and heuristic algorithm are verified by experiments.
基金supported by the National Natural Science Foundation of China(7180121871701067+3 种基金72071075)the Research Project of National University of Defense Technology(ZK18-03-16)the Natural Science Foundation of Hunan Province,China(2020JJ46722019JJ50039)。
文摘Most earth observation satellites(EOSs)are low-orbit satellites equipped with optical sensors that cannot see through clouds.Hence,cloud coverage,high dynamics,and cloud uncertainties are important issues in the scheduling of EOSs.The proactive-reactive scheduling framework has been proven to be effective and efficient for the uncertain scheduling problem and has been extensively employed.Numerous studies have been conducted on methods for the proactive scheduling of EOSs,including expectation,chance-constrained,and robust optimization models and the relevant solution algorithms.This study focuses on the reactive scheduling of EOSs under cloud uncertainties.First,using an example,we describe the reactive scheduling problem in detail,clarifying its significance and key issues.Considering the two key objectives of observation profits and scheduling stability,we construct a multi-objective optimization mathematical model.Then,we obtain the possible disruptions of EOS scheduling during execution under cloud uncertainties,adopting an event-driven policy for the reactive scheduling.For the different disruptions,different reactive scheduling algorithms are designed.Finally,numerous simulation experiments are conducted to verify the feasibility and effectiveness of the proposed reactive scheduling algorithms.The experimental results show that the reactive scheduling algorithms can both improve observation profits and reduce system perturbations.
