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Applications of An Improved Ant Colony Optimization ACO Algorithm in Integrated Process Planning and Scheduling

Abstract: The improvement of standard ant colony optimization (ACO) strategy is important#br# to improve the quality and efficiency for integrated process planning and scheduling (IPPS). A#br# graph-based optimization model for IPPS is constructed by means of node set, directed arc#br# set/undirected arc set and relation of AND/OR. An improved ACO for IPPS is proposed, which#br# avoids the slow convergence and the local convergence by dynamic pheromone update strategy,#br# and improves the quality by multi-objective optimization strategy. The simulation result#br# demonstrates the validity of the proposed algorithm for IPPS.#br# Key words: process planning; scheduling; integration; optimization; ant colony optimization   

  • Online:2015-06-30 Published:2015-05-05

Abstract: The improvement of standard ant colony optimization (ACO) strategy is important
to improve the quality and efficiency for integrated process planning and scheduling (IPPS). A
graph-based optimization model for IPPS is constructed by means of node set, directed arc
set/undirected arc set and relation of AND/OR. An improved ACO for IPPS is proposed, which
avoids the slow convergence and the local convergence by dynamic pheromone update strategy,
and improves the quality by multi-objective optimization strategy. The simulation result
demonstrates the validity of the proposed algorithm for IPPS.

Key words: process planning, scheduling, integration, optimization, ant colony optimization