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Title: Optimization of process plans using a constraint-based tabu search approach
Authors: Li, W.D.
Ong, S.K. 
Nee, A.Y.C. 
Issue Date: 15-May-2004
Citation: Li, W.D., Ong, S.K., Nee, A.Y.C. (2004-05-15). Optimization of process plans using a constraint-based tabu search approach. International Journal of Production Research 42 (10) : 1955-1985. ScholarBank@NUS Repository.
Abstract: A computer-aided process planning system should ideally generate and optimize process plans to ensure the application of good manufacturing practices and maintain the consistency of the desired functional specifications of a part during its production processes. Crucial processes, such as selecting machining resources, determining set-up plans and sequencing operations of a part should be considered simultaneously to achieve global optimal solutions. In this paper, these processes are integrated and modelled as a constraint-based optimization problem, and a tabu search-based approach is proposed to solve it effectively. In the optimization model, costs of the utilized machines and cutting tools, machine changes, tool changes, set-ups and departure from good manufacturing practices (penalty function) are the optimization evaluation criteria. Precedence constraints from the geometric and manufacturing interactions between features and their related operations in a part are denned and classified according to their effects on the plan feasibility and processing quality. A hybrid constraint-handling method is developed and embedded in the optimization algorithm to conduct the search efficiently in a large-size constraint-based space. Case studies, which are used for comparing this approach with the genetic algorithm and simulated annealing approaches, and the proposed constraint-handling method and other constraint methods, are discussed to highlight the performance of this approach in terms of the solution quality and computational efficiency of the algorithm.
Source Title: International Journal of Production Research
ISSN: 00207543
DOI: 10.1080/00207540310001652897
Appears in Collections:Staff Publications

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