Advanced scatter search approach and its application in a sequencing problem of mixed-model assembly lines in a case company

Abstract

Mixed-model assembly line sequencing is significant in reducing the production time and overall cost of production. To improve production efficiency, a mathematical model aiming simultaneously to minimize overtime, idle time and total set-up costs is developed. To obtain high-quality and stable solutions, an advanced scatter search approach is proposed. In the proposed algorithm, a new diversification generation method based on a genetic algorithm is presented to generate a set of potentially diverse and high-quality initial solutions. Many methods, including reference set update, subset generation, solution combination and improvement methods, are designed to maintain the diversification of populations and to obtain high-quality ideal solutions. The proposed model and algorithm are applied and validated in a case company. The results indicate that the proposed advanced scatter search approach is significant for mixed-model assembly line sequencing in this company.

Keywords:

• scatter search approach
• genetic algorithms
• mixed-model assembly line
• sequencing problem

Additional information

Funding

This work is supported by the State Key Program of National Natural Science of China [grant no. 51035001]; National Natural Science Foundation of China [grant no. 51275190]; National Science and Technology Major Project of China [grant no. 2011ZX04015-011-07]; and the Fundamental Research Funds for the Central Universities.