بهینه سازی یکپارچه برنامه ریزی تولید و برنامه ریزی در خط مونتاژ مدل مختلط

In order to solve the separation in the traditional serial production planning and scheduling in mixed model assembly line, the integrated optimization complete model of production planning and scheduling based on multiple objectives and constraints was constructed. Since the integrated optimization complete model is difficult to solve, the heuristic approach was adopt, and the modified discrete particle swarm optimization(MDPSO) was presented to solve the model. The experiments verifies the presented model and algorithm can realize the simultaneously optimization of production planning and scheduling in mixed model assembly line and contribute to performance improvement and the application scope expand of the new intelligent optimization.

In the actual production environment, production planning and scheduling are closely linked and interacted. However, in the traditional serial production planning and scheduling, the two levels are split. In order to eliminate the separation, the integrated optimization modelling of production planning and scheduling is presented. As the final production unit, the mixed model assembly line takes a very important role in manufacturing system. Therefore, in this paper, the integrated optimization of production planning and scheduling in he mixed model assembly line was studied The integrated optimization of production planning and scheduling can be divided into 4 categories[1]. The complete model is one of them, namely construct the integrated optimization model of production planning and scheduling directly and can describe problems precisely. Therefore, in this paper, the complete integrated optimization model of production planning and scheduling in mixed model assembly line will be proposed. Complete integrated model is very difficult to solve, we select the heuristic method to solve it. The studies on integrated optimization in assembly line are seldom. Yan et al. [2] presented three heuristic methods to achieve simultaneously optimization of production planning and scheduling in assembly line. L. Chen et al[3] used the heuristic method to optimize the production planning and scheduling simultaneously in assembly shops. Particle swarm optimization(PSO) is an evolutionary computation algorithm based on populations[4] in 1995. PSO is an excellent optimization algorithm in continuous space which has many advantages. The integrated optimization of production planning and scheduling is discrete combination optimization. However, PSO should be modified to adapt the discrete combination optimization. Currently, the discretization strategies of PSO can be divided into three categories: (1) take the speed as the probability of position changes[5,6]. (2)redefine the PSO operations [7]. (3)apply in discrete situation [8] directly. Different from the above methods, we will present new encoding and decoding scheme to achieve algorithm discretization and improve the algorithm performance. The modified discrete particle swarm optimization(MDPSO) will be proposed to solve the integrated optimization model

The integrated optimization model and its solving algorithm of production planning and scheduling in mixed model assembly line were presented in this paper. (1) In the model construction, the definition of the complete integrated optimization modelling of production planning and scheduling in mixed model assembly line were proposed firstly, and then the model based on multiple objectives and constraints was constructed. (2) In the model solving, in order to overcome the difficulty in the complete integrated optimization model solving, the heuristic approach in was adopt. The encoding, decoding and evolution way of PSO was improved and the modified discrete particle swarm optimization was put forward to solve the integrated optimization model