A matheuristic for large-scale capacitated clustering

Gnägi, Mario; Baumann, Paul

doi:10.1016/j.cor.2021.105304

Cited by 24 publications

(7 citation statements)

References 42 publications

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“…In addition, literature [11] applied the proposed method GB21 MH to CCCP and gave experimental results. Table 7 shows the comparative experimental results of A-BRKGA_ INLS and GB21 MH .…”

Section: Diffmentioning

confidence: 99%

“…Baumann [10] presented an extended version of K-Means, which uses binary linear programming to assign points to clusters. In the latest paper of CPMP [11], the author proposes a decomposition strategy for solving large-scale instances. In the local optimization stage, the new IRMA reduction method is used, in which priority is given to sub-problems with great potential to increase the objective function value.…”

Section: Introductionmentioning

confidence: 99%

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An Iterative Neighborhood Local Search Algorithm for Capacitated Centered Clustering Problem

Guo

Zeng

2022

IEEE Access

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The Capacitated Centered Clustering Problem (CCCP) is NP-hard and has many practical applications. In recent years, many excellent CCCP solving algorithms have been proposed, but their ability to search in the neighborhood space of clusters is still insufficient. Based on the adaptive Biased Random-Key Genetic Algorithm (A-BRKGA), this paper proposes an efficient iterative neighborhood search algorithm A-BRKGA_INLS. The algorithm uses shift and swap heuristics to search neighborhood space iteratively to enhance the quality of solutions. The computational experiments were conducted in 53 instances. A-BRKGA_INLS improves the best-known solutions in 23 instances and matches the best-known solutions in 15 instances. Moreover, it achieves better average solutions on multiple instances while spending the same time as the A-BRKGA+CS.

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“…In addition, literature [11] applied the proposed method GB21 MH to CCCP and gave experimental results. Table 7 shows the comparative experimental results of A-BRKGA_ INLS and GB21 MH .…”

Section: Diffmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Iterative Neighborhood Local Search Algorithm for Capacitated Centered Clustering Problem

Guo

Zeng

2022

IEEE Access

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“…As a solution procedure, a hybrid multi-start metaheuristic with tabu search and path relinking is presented. Gnägi and Baumann [14] introduced a new matheuristic for the capacitated 𝑝-median problem. This solution procedure is composed of two phases: a global optimization phase, aiming to generate an initial feasible solution, and a local optimization phase, aiming to improve this initial solution.…”

Section: Related Approachesmentioning

confidence: 99%

Hybrid matheuristics for the multi-capacitated clustering problem

2022

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The capacitated clustering problem is a well-known and largely studied combinatorial optimization problem with several industrial applications. Although a great attention has been paid to this problem in the literature, the deeming of the problem with clients of multiple types and clusters with multiple capacities is quite limited. We introduce a novel variant of capacitated clustering problems named multi-capacitated clustering problem (MCCP), a NP-hard optimization problem in which there are several clients that must be grouped into different sets that have different capacities for different types of clients. It is taken into account the distance between each one of these clients and the potential clusters to which they can be allocated, aiming to minimize the sum of such distances. It is presented an integer programming model for this problem, which it is shown to have limited application solving large-sized instances. As solution procedures, we present the following algorithms. We propose a greedy heuristic to generate a feasible solution within a negligible computational effort. We adapt a size-reduction (SR) matheuristic to solve the problem under study. Furthermore, we introduce an innovative matheuristic that hybridizes the well-known GRASP algorithm with the SR algorithm. Also, we develop a variable fixing (VF) heuristic, which is an extension of the matheuristic presented by Martinez-Gavara et al. \cite{martinez2017randomized}. Finally, we propose a hybrid matheuristic based on the SR and VFH algorithms. Computational results over a set of 100 randomly generated test instances point out the quality of the solutions found by the proposed algorithms. Our proposals are among the best heuristics developed for this problem.

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“…This formulation can be solved to optimality for small instances (up to 1000 demand/facility nodes) by exact solution approaches. For larger instances, the required time of these exact approaches becomes prohibitively large and numerous heuristic (classic-, meta-and math-heuristic) solution approaches have been proposed (Gnagi and Baumann, 2021).…”

Section: Capacitated P-median Model For Optimal Micro-hub Locationmentioning

confidence: 99%

Optimal Location Analysis of Micro Distribution Centers for Last Mile Delivery

Knežević¹,

Milenković²,

Bojović³

2021

Zbornik Radova Trideset Devetog Simpozijuma O Novim Tehnologijama U Poštanskom I Telekomunikacionom Saobraćaju – Postel 2021

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Last mile delivery represents an intensely competitive business and the position of postal companies, as a traditional provider of this service, is under the increasing pressure. The aim of this paper is to provide a review of the current process of parcel deliveries of Public Enterprise Post of Serbia and to assess the possibility for introduction of alternative models. More precisely, for Belgrade urban area, we analyze the potential for transition from the current hub-and-spoke model to a multy hub distributed last mile delivery model which will be based on e-cycle logistics. Optimal location of micro hubs for last mile deliveries is formulated as a capacitated p-median problem. Proposed approach enables decision makers in postal sector to understand and conduct appropriate actions towards redesigning the current last mile logistics service to a new green logistics solution.

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A matheuristic for large-scale capacitated clustering

Cited by 24 publications

References 42 publications

An Iterative Neighborhood Local Search Algorithm for Capacitated Centered Clustering Problem

An Iterative Neighborhood Local Search Algorithm for Capacitated Centered Clustering Problem

Hybrid matheuristics for the multi-capacitated clustering problem

Optimal Location Analysis of Micro Distribution Centers for Last Mile Delivery

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