The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problem

This article introduces methods for initializing a single-trajectory-based metaheuristic, specifically a simulated annealing (SA) algorithm, using constructive heuristics. These methods are designed to target promising regions within the search space of an nondeterministic polynomial time (NP)-hard...

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Main Authors: Abdul Kader Kassoumeh, Zühal Kartal, Ahmet Arslan
Format: Article
Language:English
Published: PeerJ Inc. 2025-06-01
Series:PeerJ Computer Science
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Online Access:https://peerj.com/articles/cs-2840.pdf
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author Abdul Kader Kassoumeh
Zühal Kartal
Ahmet Arslan
author_facet Abdul Kader Kassoumeh
Zühal Kartal
Ahmet Arslan
author_sort Abdul Kader Kassoumeh
collection DOAJ
description This article introduces methods for initializing a single-trajectory-based metaheuristic, specifically a simulated annealing (SA) algorithm, using constructive heuristics. These methods are designed to target promising regions within the search space of an nondeterministic polynomial time (NP)-hard problem, namely the single allocation p-hub center and routing problem. The objective of this problem is to allocate demand centers to hubs and design vehicle routes such that the maximum distance between all origin-destination pairs is minimized. To analyze the impact of different initial solutions, various constructive heuristics, including greedy and hybrid strategies, have been proposed. Additionally, a problem decomposition approach leveraging domain-specific knowledge has been incorporated through a matheuristic initial solution strategy to enhance the efficiency of the simulated annealing algorithm. This approach generates high-quality initial solutions by first solving the p-hub center problem and then using the obtained hubs and their assignments as inputs to the min-max multiple traveling salesman problem. In this problem, the objective function is formulated differently from the literature by minimizing the longest distance between the two nodes. Several experiments have been conducted on the Turkish network, and upon examining the results, it has been observed that each initial solution generation strategy provides improvements in problem instances with specific characteristics, such as the number of vehicles and nodes. We also observed lower objective function values for all medium- and large-sized test problems taken from the literature, highlighting the effectiveness of the proposed strategies.
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spelling doaj-art-99a9bbff21ff418caee863cdd8a0e2aa2025-08-20T03:24:22ZengPeerJ Inc.PeerJ Computer Science2376-59922025-06-0111e284010.7717/peerj-cs.2840The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problemAbdul Kader Kassoumeh0Zühal Kartal1Ahmet Arslan2Department of Computer Science, Eskisehir Technical University, Eskisehir, TurkiyeDepartment of Industrial Engineering, Eskisehir Technical University, Eskisehir, TurkiyeDepartment of Computer Science, Eskisehir Technical University, Eskisehir, TurkiyeThis article introduces methods for initializing a single-trajectory-based metaheuristic, specifically a simulated annealing (SA) algorithm, using constructive heuristics. These methods are designed to target promising regions within the search space of an nondeterministic polynomial time (NP)-hard problem, namely the single allocation p-hub center and routing problem. The objective of this problem is to allocate demand centers to hubs and design vehicle routes such that the maximum distance between all origin-destination pairs is minimized. To analyze the impact of different initial solutions, various constructive heuristics, including greedy and hybrid strategies, have been proposed. Additionally, a problem decomposition approach leveraging domain-specific knowledge has been incorporated through a matheuristic initial solution strategy to enhance the efficiency of the simulated annealing algorithm. This approach generates high-quality initial solutions by first solving the p-hub center problem and then using the obtained hubs and their assignments as inputs to the min-max multiple traveling salesman problem. In this problem, the objective function is formulated differently from the literature by minimizing the longest distance between the two nodes. Several experiments have been conducted on the Turkish network, and upon examining the results, it has been observed that each initial solution generation strategy provides improvements in problem instances with specific characteristics, such as the number of vehicles and nodes. We also observed lower objective function values for all medium- and large-sized test problems taken from the literature, highlighting the effectiveness of the proposed strategies.https://peerj.com/articles/cs-2840.pdfP-hub center problemP-hub center and routing problemMatheuristicsSimulated annealing
spellingShingle Abdul Kader Kassoumeh
Zühal Kartal
Ahmet Arslan
The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problem
PeerJ Computer Science
P-hub center problem
P-hub center and routing problem
Matheuristics
Simulated annealing
title The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problem
title_full The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problem
title_fullStr The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problem
title_full_unstemmed The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problem
title_short The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problem
title_sort effect of different initial solutions on the metaheuristic algorithms for the single allocation p hub center and routing problem
topic P-hub center problem
P-hub center and routing problem
Matheuristics
Simulated annealing
url https://peerj.com/articles/cs-2840.pdf
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