Abstract
Although production and transportation scheduling problems are of two essential issues in supply chain management, they are rarely integrated. In this paper, we study the problem of production and transportation scheduling to minimize total cost of supply chain. The problem is mathematically modeled. Moreover, a novel metaheuristic based on an imperialist competitive algorithm is developed for solving the problem. The proposed algorithm is enriched by a chaotic map and two new operators to avoid from local optima. To tune the parameters, Taguchi experimental design is applied. For evaluation of the proposed algorithm, it is compared with an available genetic algorithm. Finally, using numerical experiments, the outperformance of the proposed algorithm is shown in both solution quality and performance robustness.
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