A multi-population genetic algorithm for transportation scheduling |
| |
Authors: | SH Zegordi MA Beheshti Nia |
| |
Institution: | aIndustrial Engineering Department, Tarbiat Modares University, Tehran 14115-143, Iran |
| |
Abstract: | This study considers the integration of production and transportation scheduling in a two-stage supply chain environment. The objective function minimizes the total tardiness and total deviations of assigned work loads of suppliers from their quotas. After modeling the problem as a mixed integer programming problem, a genetic algorithm with three populations, namely, a multi-society genetic algorithm (MSGA), is proposed for solving it. MSGA is compared with the optimum solutions for small problems and a heuristic and a random search approach for larger problems. Additionally, an MSGA is compared with a generic genetic algorithm. The experimental results show the superiority of the MSGA. |
| |
Keywords: | Scheduling Supply chain management Genetic algorithm Transportation Tardiness |
本文献已被 ScienceDirect 等数据库收录! |
|