Multi-Objective Optimization and Multi-Attribute Decision Making for a Novel Batch Scheduling Problem Based on Mould Capabilities

  • Jun Pei
  • Athanasios Migdalas
  • Wenjuan Fan
  • Xinbao Liu
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 130)

Abstract

This chapter investigates a novel multi-objective model of a batch scheduling problem with constraint of the mould capability, and the objective is to minimize both the total completion time of the jobs and the total cost of the moulds. It is extremely difficult to obtain an optimal solution to this type of complex problems in a reasonable computational time. In view of this, this chapter presents a new multi-objective algorithm based on the features of Gravitational Search Algorithm to find Pareto optimal solutions for the given problem. In the proposed algorithm a novel Pareto frontier adjustment strategy is designed and proven to improve the convergence of solutions and increase convergence speed. We examined a set of test problems to validate the high efficiency of the proposed multi-objective gravitational search algorithm based on a variety of metrics. Finally, a multi-attribute decision making method is employed to determine the trade-off solutions derived from the Pareto optimal set and thus solve the problem optimally.

Keywords

Batch scheduling Mould capability Gravitational search algorithm Technique for order preference by similarity to ideal solution (TOPSIS) 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jun Pei
    • 1
    • 2
  • Athanasios Migdalas
    • 3
    • 4
  • Wenjuan Fan
    • 5
    • 6
  • Xinbao Liu
    • 5
    • 6
  1. 1.Department of Information Management and Information Systems, School of ManagementHefei University of TechnologyHefeiChina
  2. 2.Department of Industrial and Systems Engineering, Center for Applied OptimizationUniversity of FloridaFLUSA
  3. 3.Industrial Logistics, ETS InstituteLuleå University of TechnologyLuleåSweden
  4. 4.Division of Transportation, Construction Management and Regional Planning, Department of Civil EngineeringAristotle University of ThessalonikiThessalonikiGreece
  5. 5.Department of Information Management and Information SystemsSchool of Management, Hefei University of TechnologyHefeiChina
  6. 6.Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of EducationHefeiChina

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