A two-stage approach based on Ant Colony Optimization Algorithm for Integrated Process Planning and Scheduling

نویسندگان

  • Sicheng Zhang
  • T. N. Wong
  • Luping Zhang
  • S. Y. Wan
چکیده

This paper presents a two-stage heuristic using Ant Colony Optimization (ACO) to solve Integrated Process Planning and scheduling (IPPS) problem. The algorithm is incorporated with the objective of obtaining an optimal or near optimal schedule for a number of jobs with multi-operations. A graphical search method is used, where artificial ants are assigned as software agents to search for routines corresponding to schedules. A new approach is attempted in this paper in which the ACO solution process has been separated into two stages. Criteria including makespan and CPU time are used as measurements of performance. Illustrative examples are given to make comparisons with former research.

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تاریخ انتشار 2011