An Improved Iterated Local Search Algorithm For Type-?Mixed-model Two-sided Assembly Line Balancing Problem

Compared with the single-model assembly line,the mixed-model two-sides assembly line is widely used in manufacturing enterprises.Study of mixed-model two-sided assembly line balancing problem can improve productivity and reduce cost.In this paper,Aiming at the type ? mixed-model two-sided assembly line balancing problem to do the research of the following work:First of all,According to the characteristics of the mixed-model two-sides assembly line,A mathematical model for type ? mixed-model two-sides assembly line balancing problem is built with the objective of minimizing the number of stations and minimizing the number of mated-stations.At the same time,the new secondary objective is designed to distinguish the solutions with the same number of stations and mated-stations but the specific allocation schemes are different in the algorithm optimization process.Then,To solve type ? mixed-model two-sided assembly line balancing problems,Study of common intelligent algorithm to find the right algorithm to solve the problem.In the process of algorithm research,considering the complex precedence relation among tasks,a workstation based decoding method and an operation based decoding method are proposed.Furthmore,in order to guarantee the performance of the initial solution,the NEH heuristic initialization method and the random key initialization method are studied.Finally,Solving all cases of type ? mixed-model two-sided assembly line balancing problems,The effectiveness and superiority of the proposed method are verified by analyzing the experimental results and decoding performance.At the same time,through the analysis of variance to check all the algorithms of each parameter,so as to choose the optimal parameter combination,which provides a reliable scientific basis for algorithm parameter selection.