Hybridization of Metaheuristics for Multi-Objective Aggregate Production Planning with Desirability Function on Food-Beverage Demand
The aggregate production planning with various demand levels based on desirability function approach in a single site and continuous food-beverage industry is addressed in this work. A multi-objective linear programming model, based on the definition of all families of products, is developed for the problem in question. Workforce balances are realized for every specific product, thus permitting the detailed optimization of production, inventory costs and labor level change. The efficiency and the applicability of the hybridizations of the bee algorithm and various stochastic operators are demonstrated by solving to near optimality for a food-beverage manufacturer in Thailand. Using a popular tool and technique for the overall satisfaction measurement, the desirability function approach is capable of simplifying the process of collecting data making it far easier to implement than the individual objective. A study showed that the proposed hybridizations are capable of returning acceptable results, compared to the bee algorithm. In conclusion, the proposed hybridizations provide a more practical implementation, while maintaining simplification power on par with the conventional bee algorithm.
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Document Type: Research Article
Publication date: December 1, 2013
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