A new approach to the joint order batching and picker routing problem with alternative locations

Author:

Hedayati Sajjad1,Setak Mostafa1,Demir Emrah234ORCID,Van Woensel Tom5

Affiliation:

1. Faculty of Industrial Engineering, K.N. Toosi University of Technology , Tehran , Iran

2. Panalpina Centre for Manufacturing and Logistics Research , Cardiff Business School, , Cardiff , UK

3. Cardiff University , Cardiff Business School, , Cardiff , UK

4. Department of Engineering Systems and Management, Khalifa University , Abu Dhabi , United Arab Emirates

5. School of Industrial Engineering, Eindhoven University of Technology , Eindhoven , The Netherlands

Abstract

Abstract The clustered and generalized vehicle routing problem (CGVRP) extends the well-known vehicle routing problem by grouping the demand points into multiple distinct zones, and within each zone, further separation is made by forming clusters. The objective of the CGVRP is to determine the optimal routes for a fleet of vehicles dispatched from a depot, visiting all zones within each cluster. This requires making two simultaneous optimization decisions. Firstly, each zone must be visited by exactly one node, and secondly, all zones within a cluster must be visited by the same vehicle. In this paper, we introduce two mixed-integer linear programming formulations for the CGVRP, aimed at solving a joint order batching and picker routing problem with alternative locations in a warehouse environment featuring mixed-shelves configuration. Both formulations are tested on three scenarios of randomly generated small- and medium-sized instances. Additionally, we propose a general rule approach for calculating a cost matrix in a rectangular environment. The results demonstrate the effectiveness of the proposed mathematical formulations in efficiently solving problems with up to 180 nodes.

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Management Science and Operations Research,Strategy and Management,General Economics, Econometrics and Finance,Modeling and Simulation,Management Information Systems

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