Multi-objective optimization of production scheduling with evolutionary computation: A review
- 1 January 2020
- journal article
- review article
- Published by Growing Science in International Journal of Industrial Engineering Computations
- Vol. 11 (3), 359-376
- https://doi.org/10.5267/j.ijiec.2020.1.003
Abstract
Multi-Objective (MO) optimization is a well-known research field with respect to the complexity of production planning and scheduling. In recent years, many different Evolutionary Computation (EC) methods have been applied successfully to MO production planning and scheduling. This paper is focused on making a review of MO production scheduling methods, starting from production scheduling presentation, notation and classification. The research field of EC methods is presented, then EC algorithms' classification is introduced for the purpose of production scheduling optimization. As a main goal, MO optimization is focused on hybrid EC methods, and presenting their advantages and limitations. Finally, a survey of five scientific databases is presented, with the analysis of the scientific publications the terminology development of the scientific field is presented. Using the citation analysis of the scientific publications, the application for the MO optimization in manufacturing scheduling is discussed. (C) 2020 by the authors; licensee Growing Science, CanadaKeywords
This publication has 67 references indexed in Scilit:
- Scheduling parallel Kalman filters for multiple processesAutomatica, 2013
- A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatchInformation Sciences, 2012
- Intelligent water drops algorithmInternational Journal of Intelligent Computing and Cybernetics, 2008
- Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problemsComputers & Industrial Engineering, 2008
- Ant colony optimization system for a multi-quantitative and qualitative objective job-shop parallel-machine-scheduling problemInternational Journal of Production Research, 2008
- Measuring the impact of Lean tools on the cost–time investment of a product using cost–time profilesRobotics and Computer-Integrated Manufacturing, 2007
- A hybrid multi-objective immune algorithm for a flow shop scheduling problem with bi-objectives: Weighted mean completion time and weighted mean tardinessInformation Sciences, 2007
- An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problemsComputers & Industrial Engineering, 2005
- Job scheduling with dual criteria and sequence-dependent setups: mathematical versus genetic programmingOmega, 2004
- A multi-objective genetic local search algorithm and its application to flowshop schedulingIEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 1998