A Variable Neighbourhood Monte Carlo Search for Component Placement Sequencing of Multi-Head Placement Machine
نویسندگان
چکیده
This work considers the optimisation of component placement sequencing to improve the efficiency of theoretical multi-head surface mount device placement machines in printed circuit board assembly. We develop a Variable Neighbourhood Monte Carlo Search (VNMS), which employs a variable neighbourhood search technique with an Exponential Monte Carlo acceptance criterion. VNMS is a descent-ascent heuristic that operates on three sets of neighbourhood structures that are based on three different local search operators. The first two sets use a steepest descent and Exponential Monte Carlo local search, respectively whilst the third set uses a random 3-opt operator. The solution returned by a local search after exploring a neighbourhood structure will be accepted based on the EMCQ (Exponential Monte Carlo with counter) acceptance criterion. The novelties of the VNMS approach (in the context of VNS) are the concept of three stages of neighbourhood search and using an EMCQ acceptance criterion at the VNS level. The shaking procedure is only applied when the local searchers cannot find an improved solution. Results show that the VNMS consistently produces a good quality solution.
منابع مشابه
A Variable Neighbourhood Search for Component Pick-and- Place Sequencing in Printed Circuit Board Assembly
This work presents a heuristic for component pick-and-place sequencing to improve the throughput of a multi-head surface mount device placement machine for assembling printed circuit board. We present a Variable Neighbourhood Monte Carlo Search (VNMS), which employs variable neighbourhood search with an Exponential Monte Carlo acceptance criterion. VNMS is a descent-ascent heuristic that operat...
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