Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/20362
Title: Modeling and Pareto optimization of multi-objective order scheduling problems in production planning
Authors: Guo, ZX
Wong, WK 
Li, Z
Ren, P
Keywords: Mathematical model
Multi-site order scheduling
NSGA-II
Pareto optimization
Production planning
Simulation model
Issue Date: 2013
Publisher: Pergamon Press
Source: Computers and industrial engineering, 2013, v. 64, no. 4, p. 972-986 How to cite?
Journal: Computers and industrial engineering 
Abstract: This paper addresses a multi-objective order scheduling problem in production planning under a complicated production environment with the consideration of multiple plants, multiple production departments and multiple production processes. A Pareto optimization model, combining a NSGA-II-based optimization process with an effective production process simulator, is developed to handle this problem. In the NSGA-II-based optimization process, a novel chromosome representation and modified genetic operators are presented while a heuristic pruning and final selection decision-making process is developed to select the final order scheduling solution from a set of Pareto optimal solutions. The production process simulator is developed to simulate the production process in the complicated production environment. Experiments based on industrial data are conducted to validate the proposed optimization model. Results show that the proposed model can effectively solve the order scheduling problem by generating Pareto optimal solutions which are superior to industrial solutions.
URI: http://hdl.handle.net/10397/20362
ISSN: 0360-8352
EISSN: 1879-0550
DOI: 10.1016/j.cie.2013.01.006
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