Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs

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.

Keywords:

• Operation process design
• enterprise system
• multiobjective scheduling
• deteriorating effect
• multiobjective evolutionary algorithm

ORCID

Junwei Wang http://dx.orcid/0000-0001-8895-2214

Additional information

Funding

This work was supported by the National Science Foundation for Distinguished Young Scholars of China [grant number 71325002], [grant number 61225012]; the National Nature Science Foundation of China [grant number 71001018], [grant number 71071028]; Fundamental Research Funds for the Central Universities [grant number N110204005], [grant number N130404017]; and Fundamental Research Funds for State Key Laboratory of Synthetical Automation for Process Industries [grant number 2013ZCX11], [grant number PAL-N201505].