Abstract
The concrete delivery problem (CDP) is an NP-hard, real world combinatorial optimization problem. The CDP involves tightly interrelated routing and scheduling constraints that have to be satisfied by considering the tradeoff between production and distribution costs. Various exact and heuristic methods have been developed to address the CDP. However, due to the limitation of the exact methods for dealing with such a complex problem, (meta-)heuristics have been more popular. For this purpose, the present study proposes a hybrid algorithm combining simulated annealing (SA) with a time-slot heuristic (TH) for tackling the CDP. The TH is applied for generating new solutions through perturbation while simulated annealing is utilized to decide on whether to accept these solutions. The proposed algorithm, i.e. SA-TH, is compared to an existing CDP heuristic on a diverse set of CDP benchmarks. The computational results conducted through a series of experiments validate the efficiency and success of SA-TH.
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Acknowledgment
This work was supported in part by the National Natural Science Foundation of China (NSFC) under grant 61300159, by the Natural Science Foundation of Jiangsu Province of China under grant BK20130808 and by China Postdoctoral Science Foundation under grant 2015M571751. The authors thank J. Kinable, T. Wauters and G. Vanden Berghe, for providing their CDP source code.
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Sulaman, M., Cai, X., Mısır, M., Fan, Z. (2017). Simulated Annealing with a Time-Slot Heuristic for Ready-Mix Concrete Delivery. In: Shi, Y., et al. Simulated Evolution and Learning. SEAL 2017. Lecture Notes in Computer Science(), vol 10593. Springer, Cham. https://doi.org/10.1007/978-3-319-68759-9_4
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