Small World Optimization for Multiple Objects Optimization of Mixed-Model Assembly Sequencing Problem

Abstract

With the continuously accelerating of economic globalization and subdividing of product demand, the production mode in manufacturing industry is always evolving. As the diversity and rapid changes of customer needs increasing, as the competition among enterprises with unprecedented speed and intensity expanding in global range, with the shorten lifecycle of product technology and market, the large-scale production with the characteristics of single variety, high-volume, continuous, and lacking of flexibility cannot meet the demands of current and future market, and the flexible production of small batch and multi-variety products, which are certain scaled and customer-oriented, have been favored in industry. The evolution of production mode has generated the mixed assembly line. Products of different types and yields have been produced on the same assembly line by changing the organization of production without changing the existing production conditions and capacity, to meet the personalized demands of different consumers in the shortest possible time and quick response to the changes of market demands, then improve the competitiveness of enterprises. Sequencing problem is one of the key issues of effectiveness on the mixed model assembly line, which determines the processing order of different products on the assembly line. A reasonable sort of production has important significance to improve production efficiency, reducing waste of resources and increasing competitiveness of enterprise in a market economy. Sequencing problem is a typical combinatorial optimization problem. Exact approach and Heuristic method (Solnon et al., 2008) have been generally used to solve such problems. Exact approach generally includes Constraint Program, Integer Program and branch and bound algorithm. And Heuristic Approach involves Greedy Approach, Local Search Approach, Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization (Chao-Tang & Ching-Jong, 2008). The computational complexity of sequencing problems has often grown exponentially, and the exact solution is difficult to deal with the traditional larger-scale problem, so in recent years Heuristic Approach has been the best approach to solve the sequencing problem. Johnson's paper (Johnson, 1954) in 1954 is the first research on sequencing problem. Classical sequencing problem has been studied widely in last 30 years. For the production