Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs. Issue 3 (23rd March 2016)

• Record Type: Journal Article
• Authors: Wang, Hongfeng; Fu, Yaping; Huang, Min; Wang, Junwei
• Is Part Of: Enterprise information systems. Volume 10:Issue 3(2016)
• Page Start: 268
• Page End: 285
• Publication Date: 2016-03-23
• Subjects: Operation process design -- enterprise system -- multiobjective scheduling -- deteriorating effect -- multiobjective evolutionary algorithm; Information storage and retrieval systems -- Periodicals; Management information systems -- Periodicals; Electronic commerce -- Periodicals; 658.4038011
• DOI: 10.1080/17517575.2015.1078913
• Languages: English
• ISSNs: 1751-7575

Abstract

Abstract : The operation process design is one of the key issues in the manufacturing and service sectors. As a typical operation process, the scheduling with consideration of the deteriorating effect has been widely studied; however, the current literature only studied single function requirement and rarely considered the multiple function requirements which are critical for a real-world scheduling process. In this article, two function requirements are involved in the design of a scheduling process with consideration of the deteriorating effect and then formulated into two objectives of a mathematical programming model. A novel multiobjective evolutionary algorithm is proposed to solve this model with combination of three strategies, i.e. a multiple population scheme, a rule-based local search method and an elitist preserve strategy. To validate the proposed model and algorithm, a series of randomly-generated instances are tested and the experimental results indicate that the model is effective and the proposed algorithm can achieve the satisfactory performance which outperforms the other state-of-the-art multiobjective evolutionary algorithms, such as nondominated sorting genetic algorithm II and multiobjective evolutionary algorithm based on decomposition, on all the test instances.