The intense competition in the current marketplace ha s forced firms to reexamine their methods of doing business, using superior manu facturing practices in the form of just-in-time (JIT), production with JIT pra cti...The intense competition in the current marketplace ha s forced firms to reexamine their methods of doing business, using superior manu facturing practices in the form of just-in-time (JIT), production with JIT pra ctices pursue completion on time and zero inventory, which is often instruct ed according to the custom’s demand or the sale contract. Earliness and tardine ss are undesirable because both of them will bring the extra cost, cost will als o be increased by some factors such as operation condition, intermediate storage , clean method, etc, to minimize the total cost is often the main scheduling objective, but sometime it is most important for factories to eliminate the tar diness cost in order to maintain the commercial credit and to avoid penalty, the refore, minimum of tardiness cost becomes the first objective. It is more import ant to select a reasonable objective by the actual condition during scheduli ng. In this paper scheduling problem of chemical batch process with due date is studied, two different intermediate storage policies and two different productio n modes are also discussed, production scheduling with different intermediate st orage policy and different production mode is proposed and the result is compare d. In order to complete all products within the due date, not only earliness and tardiness but also holding problem is considered, the objective is to selec t a proper intermediate storage policy and production mode and to minimize the c ost resulted by the earliness and tardiness, even the cost result by the interme diate storage. Scheduling with multiple stage and multiple machine is known as a NP-hard problem, mathematical program (MP) method, such as branch-and-bound (BAB), mixed integer linear program (MILP), etc, is often used to solve the sche duling problem. But as is well known, MP method is not good for combination opti mization, especially for large scale and complex optimal problem, whereas geneti c algorithm (GA) can overcome the MP method’s shortcoming and is fit for solvin g such scheduling problem. In this paper a modified genetic algorithm with speci al crossover operator and mutation operator is presented to solve this schedulin g problem. The results show such problem can be solved effectively with the pres ented method.展开更多
In this paper, we give a mathematical model for earliness-tardiness job scheduling problem with a common due window on parallel and non-identical machines. Because the job scheduling problem discussed in the paper con...In this paper, we give a mathematical model for earliness-tardiness job scheduling problem with a common due window on parallel and non-identical machines. Because the job scheduling problem discussed in the paper contains a problem of minimizing make-span, which is NP-complete on parallel and uniform machines, a heuristic algorithm is presented to find an approximate solution for the scheduling problem after proving an important theorem. Two numerical examples illustrate that the heuristic algorithm is very useful and effective in obtaining the near-optimal solution.展开更多
文摘The intense competition in the current marketplace ha s forced firms to reexamine their methods of doing business, using superior manu facturing practices in the form of just-in-time (JIT), production with JIT pra ctices pursue completion on time and zero inventory, which is often instruct ed according to the custom’s demand or the sale contract. Earliness and tardine ss are undesirable because both of them will bring the extra cost, cost will als o be increased by some factors such as operation condition, intermediate storage , clean method, etc, to minimize the total cost is often the main scheduling objective, but sometime it is most important for factories to eliminate the tar diness cost in order to maintain the commercial credit and to avoid penalty, the refore, minimum of tardiness cost becomes the first objective. It is more import ant to select a reasonable objective by the actual condition during scheduli ng. In this paper scheduling problem of chemical batch process with due date is studied, two different intermediate storage policies and two different productio n modes are also discussed, production scheduling with different intermediate st orage policy and different production mode is proposed and the result is compare d. In order to complete all products within the due date, not only earliness and tardiness but also holding problem is considered, the objective is to selec t a proper intermediate storage policy and production mode and to minimize the c ost resulted by the earliness and tardiness, even the cost result by the interme diate storage. Scheduling with multiple stage and multiple machine is known as a NP-hard problem, mathematical program (MP) method, such as branch-and-bound (BAB), mixed integer linear program (MILP), etc, is often used to solve the sche duling problem. But as is well known, MP method is not good for combination opti mization, especially for large scale and complex optimal problem, whereas geneti c algorithm (GA) can overcome the MP method’s shortcoming and is fit for solvin g such scheduling problem. In this paper a modified genetic algorithm with speci al crossover operator and mutation operator is presented to solve this schedulin g problem. The results show such problem can be solved effectively with the pres ented method.
基金Zhejiang Provincial Natural Science Foundation (No. 698069) and High-Tech. Research andDevelopment Program (No. 863-511-945-002)
文摘In this paper, we give a mathematical model for earliness-tardiness job scheduling problem with a common due window on parallel and non-identical machines. Because the job scheduling problem discussed in the paper contains a problem of minimizing make-span, which is NP-complete on parallel and uniform machines, a heuristic algorithm is presented to find an approximate solution for the scheduling problem after proving an important theorem. Two numerical examples illustrate that the heuristic algorithm is very useful and effective in obtaining the near-optimal solution.
