A hybrid multi-objective immune algorithm for a flow shop scheduling problem with bi-objectives: Weighted mean completion time and weighted mean tardiness |
| |
Authors: | Reza Tavakkoli-Moghaddam Alireza Rahimi-Vahed |
| |
Affiliation: | a Department of Industrial Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran b Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran |
| |
Abstract: | This paper investigates a novel multi-objective model for a no-wait flow shop scheduling problem that minimizes both the weighted mean completion time and weighted mean tardiness . Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new hybrid multi-objective algorithm based on the features of a biological immune system (IS) and bacterial optimization (BO) to find Pareto optimal solutions for the given problem. To validate the performance of the proposed hybrid multi-objective immune algorithm (HMOIA) in terms of solution quality and diversity level, various test problems are examined. Further, the efficiency of the proposed algorithm, based on various metrics, is compared against five prominent multi-objective evolutionary algorithms: PS-NC GA, NSGA-II, SPEA-II, MOIA, and MISA. Our computational results suggest that our proposed HMOIA outperforms the five foregoing algorithms, especially for large-sized problems. |
| |
Keywords: | Multi-objective no-wait flow shop scheduling Completion time Tardiness Multi-objective evolutionary algorithms Immune system Bacterial optimization |
本文献已被 ScienceDirect 等数据库收录! |
|