Many optimization problems, such as manufacturing process planning optimization, are difficult problems due to the large number of potential configurations (process sequences) and associated (process) parameters. In addition, the search space is highly discontinuous and multi-modal. This paper introduces an agent based optimization algorithm that combines stochastic optimization techniques with knowledge based search. The motivation is that such a merging takes advantage of the benefits of stochastic optimization and accelerates the search process using domain knowledge. The result of applying this algorithm to computerized manufacturing process models is presented.
An Agent Based Optimization Approach to Manufacturing Process Planning
Contributed by the Design Theory and Methodology Committee for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received July 2001; rev. June 2003. Associate Editor: D. L. Thurston.
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Deshpande , S., and Cagan , J. (March 11, 2004). "An Agent Based Optimization Approach to Manufacturing Process Planning ." ASME. J. Mech. Des. January 2004; 126(1): 46–55. https://doi.org/10.1115/1.1641186
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