Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)

Volume 129 of the series Studies in Computational Intelligence pp 443-452

UPlanIT: An Evolutionary Based Production Planning and Scheduling System

  • Saeedeh Maleki-DizajiAffiliated withComputer Science Department, Manchester University
  • , Henry NyongesaAffiliated withDepartment of Computer Science, University of Botswana
  • , Babak KhazaeiAffiliated withFaculty of Arts, Computing, Engineering and Sciences, Sheffield Hallam University

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In this paper we discuss an optimization approach to a real-world production planning problem. Based on raw data from instances of production planning we have developed an architecture for optimization of production planning and scheduling for manufacturing lines in small/medium enterprises (SME). The approach referred to as “Unified Planning using Intelligent Techniques”-abbreviated UPlanIT is based on genetic algorithms (GA). The schedules are constructed using rules in which the priorities are determined by the GA, using a procedure that generates parameterized activities. The approach is tested on a set of real standard production instances. The results validate the effectiveness of the proposed algorithm.