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A Heuristic Algorithm for solving a large-scale real-world territory design problem
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DOI：10.1016/j.omega.2021.102442.png)
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Abstract
En 中文
In this work, we present and evaluate heuristic techniques for a real-world territory design problem of a major dairy company which produces and distributes perishable products. The problem calls for grouping customers into geographic districts, with the objective of minimising the total operational cost, computed as a function of the fixed costs of the districts and the routing costs. Two inter-connected decision levels have to be tackled: partitioning customers into districts and routing vehicles according to complex operational constraints. To solve the problem, a hybrid multi-population genetic algorithm is designed, enhanced with several evolution and search techniques. The proposed design is extensively tested on instances derived from the literature and on real-world large-scale instances, involving more than 10 0 0 customers. The results show the effectiveness of the different components of the algorithm and the feedback from the company's planners confirms that it produces high-quality, operational solutions. Additionally, we explore some managerial findings with respect to the adoption of alternative objectives and service requirements. (c) 2021 Elsevier Ltd. All rights reserved.
Keywords:
Territory design
Periodic vehicle routing
Hybrid genetic algorithm
Dairy industry
Real-world instances
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