Production Planning And Production Scheduling For Automobile Parts Based On Hybrid Algorithm

With the rapid development of economy, the competition in the automotive manufacturing industry is also becoming increasingly fierce. In order to survive and develop, it must have the good ability to respond and adapt complex market environment. Production planning and production scheduling is the core content and key technologies for enterprise production management, whose task is to reach the goal of economic or performance needs.This article based on the actual production situation of automobile parts, to describe the existing workshop production planning and scheduling problems. Automobile parts production is a complex combinatorial optimization problem, which is a typical NP-hard problem. Although it has been proposed many optimization methods for solving the problem, most only apply to smaller issues. Furthermore, these methods have their respective limitations. In this paper, a hybrid algorithm is proposed to solve scheduling problem.In this paper, the profit maximization of automobile parts manufacturing as the goal to research the optimization problems of automobile parts production planning. And establish integer programming model according to auto parts production processes, and on this basis establish a stochastic expected value model. This paper proposes an intelligent algorithm which combines stochastic simulation and hybrid algorithm to solve the problem of production planning for automobile parts. Numerical examples are given out to validate the model and method are reliable. In addition, the article minimize the completion time as the target to research the automobile parts job shop scheduling problem. And use hybrid algorithm which combines genetic algorithm and tabu search algorithm to research the problem, through simulation experiments to verify the reliability and effectiveness.