Affiliation:
1. School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
2. School of Electronic and Information Engineering, Tongji University, Shanghai 200092, China
3. School of Economics and Management, Anhui Normal University, Wuhu 241000, China
Abstract
The cost-reducing potential of intelligent supply chains (ISCs) has been recognized by companies and researchers. This paper investigates a two-echelon steel supply chain scheduling problem that considers the parallel-batching processing and deterioration effect in the production stage and sufficient vehicles in the port delivery stage. To solve this problem, we first analyze several sufficient and necessary conditions of the optimal scheme. We then propose a heuristic algorithm based on a dynamic programming algorithm to obtain the optimal solution for a special case where the assignment of all ingots to the soaking pits is known. Based on the results of this special case, we develop a modified biased random-key genetic algorithm (BRKGA), which incorporates genetic operations based on the flower pollination algorithm (FPA) to obtain joint production and distribution schedules for the general problem. Finally, we conduct a series of computational experiments, the results of which indicate that BRKGA-FPA has certain advantages in solving quality and convergence speed issues.
Funder
Ministry of Education of Humanities and Social Science Project
China Postdoctoral Science Foundation
Educational Commission of Anhui Province
Natural Science Foundation of Anhui Province
Anhui Province University Collaborative Innovation Project
Science and Technology Plan Project of Wuhu
National Natural Science Foundation of China
Key Research and Development Project of Anhui Province
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)