Abstract
An aggregate production-distribution model, which minimizes the regular, overtime and outsourced production costs along with inventory holding, backorder, hiring/laying-off and trip-wise distribution costs, is developed for a renowned bearing manufacturing industry in India. The proposed integer non-linear programming (INLP) problem is NP-hard and hence a discrete particle swarm optimization (DPSO) algorithm is applied to solve the multi-site, multi-period production-distribution problem. The results obtained using DPSO algorithm are compared with the results of memetic algorithm (MA), genetic algorithm (GA) and simulated annealing (SA). DPSO algorithm results are far superior to that of other meta-heuristic approaches for the problem considered.
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