An effective heuristic based on 3- opt strategy for seru scheduling problems with learning effect
研究了考虑DeJong学习效应的seru生产系统调度问题，以最小化总加权完工时间，提出了一种基于3-opt和禁忌搜索的启发式算法，实验表明该算法在解质量、效率和可扩展性方面表现良好。
This paper is concerned with the scheduling problem in a new-type seru production system by consideration of DeJong's learning effect to minimise the total weighted completion time, so as to achieve efficiency, flexibility, and fast responsiveness to cope with the current volatile market. A combinatorial optimisation model is constructed and then reformulated to a binary quadratic assignment program. Accordingly, after presenting the necessary and sufficient condition for the locally optimal solution, a tabu search with strategic oscillation based on 3-opt as a diversification strategy is designed as the solution approach. A set of test problems are generated, and computational experiments with large-scale cases are made finally. The results indicate that the proposed heuristic algorithm is promising in solving seru scheduling problems and has a good performance in term of solution quality, efficiency, and scalability.