Abstract
In this paper, we study simultaneously order acceptance and scheduling in a single machine environment. We assume the capacity of accepted orders is limited and the orders are characterized based on due dates, processing times, revenues, weights, and sequence-dependent setup times. The objective is profit maximization that is the total revenues minus total weighted tardiness. We propose a mathematical programming model and two population-based metaheuristic algorithms, biogeography-based optimization (BBO) algorithm, and genetic algorithm (GA), for solving this problem. We use Taguchi design to determine parameters values. The results of two developed algorithms are not only compared to the results of the mathematical model, but also compared to each other for determining the best algorithm. Computational results on generated instances show that the BBO algorithm outperforms GA, particularly for large size instances, in terms of the objective function.
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