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

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