The capacitated lot sizing and scheduling problem that involves in determining the production amounts and release dates for several items over a given planning horizon are given to meet dynamic order demand without incurring backloggings. The problem considering overtime capacity is studied. The mathematical model is presented, and a genetic algorithm (GA) approach is developed to solve the problem. The initial solutions are generated after using heuristic method. Capacity balancing procedure is employed to stipulate the feasibility of the solutions. In addition, a technique based on Tabu search (TS) is inserted into the genetic algorithm to deal with the scheduled overtime and help the convergence of algorithm. Computational simulation is conducted to test the efficiency of the proposed hybrid approach, which turns out to improve both the solution quality and execution speed.
Yang Honghong Wu ZhimingDepartment of Automation,Shanghai Jiaotong University,Shanghai 200030, China
An efficient algorithm for finding an optimal deadlock-free schedule in a manufacturing system with very limited buffer is presented. This algorithm is based on the effective genetic algorithm (GA) search method, and a formal Petri net structure is introduced to detect the token player assuring deadlock-free. In order to make the scheduling strategy generated by GA meet the required constraint of deadlock-free, Petri net is involved to make the implementation of the job scheduling in an FMS deadlock-free. The effectiveness and efficiency of the proposed approach is illustrated by using an example.
Xu Gang Wu ZhimingSchool of Automation,Shanghai Jiaotong University,Shanghai 200030, China
Deadlock must be avoided in a manufacturing system. In this paper, an efficient algorithm for finding an optimal deadlock-free schedules in a manufacturing system with very limited buffer is presented. This algorithm is based onhe effective genetic algorithm (GA) search method, and a formal Petri net structure is introduced to detect the token player assuring deadlock-free. In order to make the scheduling strategy generated by GA meet the required constraint of deadlock-free, some results of the strueture analysis of Petri net are involved as a criterion to select deadlock-free schedule from the population generated by GA. The effectiveness and efficiency of the proposed approach is illustrated by using an example.
