Two-Sided Assembly Line Balancing Optimization With Spider Monkey Optimization

Abstract

Growing interests from customers in customized products and increasing competition among peers necessitate companies to configure and balance their manufacturing systems more effectively than ever before. Two-sided assembly lines are usually constructed to produce large-sized high-volume products such as buses, trucks, automobiles, and some domestic products. Since the problem is well known as NP-hard problem, a mathematical model is solved by an exact solution-based approach and spider monkey optimization (SMO) algorithm that is inspired by the intelligent foraging behavior of fission-fusion social structure-based animals. In this chapter, the proposed mathematical model is applied to solve benchmark problems of two-sided assembly line balancing problem to minimize the number of mated stations and idle time. The experimental results show that spider monkey optimizations provide better results.