Solving the uncapacitated hub location problem using genetic algorithms (original) (raw)
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Genetic algorithm for solving uncapacitated multiple allocation hub location problem
2012
Abstract Hub location problems are widely used for network designing. Many variations of these problems can be found in the literature. In this paper we deal with the uncapacitated multiple allocation hub location problem (UMAHLP). We propose a genetic algorithm (GA) for solving UMAHLP that uses binary encoding and genetic operators adapted to the problem. Overall performance of GA implementation is improved by caching technique.
An evolutionary-based approach for solving a capacitated hub location problem
Applied Soft Computing, 2011
This paper addresses the capacitated hub location problem (CHLP), which is a variant of the classical capacitated hub problem. What is presented is a modified mixed integer linear programming (MILP) formulation for the CHLP. This modified formulation includes fewer variables and constraints compared to the existing problem formulations in the literature. We propose two evolutionary algorithms (EAs) that use binary encoding and standard genetic operators adapted to the problem. The overall performance of both EA implementations is improved by a caching technique. In order to solve large-scale instances within reasonable time, the second EA also uses a newly designed heuristic to approximate the objective function value. The presented computational study indicates that the first EA reaches optimal solutions for all smaller and medium-size problem instances. The second EA obtains high-quality solutions for larger problem dimensions and provides solutions for large-scale instances that have not been addressed in the literature so far.
A biased random-key genetic algorithm for the tree of hubs location problem
Hubs are facilities used to treat and dispatch resources in a transportation network. The main idea of Hub Location Problems (HLP) is to locate a number of hubs in a network and route resources from origins to destinations such that the total cost of attending all demands is minimized. In this study, we investigate a particular HLP, called the Tree of Hubs Location Problem in which hubs are connected by means of a tree and the overall network infrastructure relies on a spanning tree. This problem is particularly interesting when the total cost of building the hub backbone is high. In this paper, we propose a biased random key genetic algorithm for solving the tree of hubs location problem. Computational results show that the proposed heuristic is a robust and effective method to tackle this problem. The method was able to improve some best known solutions from the benchmark instances used in the experiments.
An Exact Solution for the Capacitated Multiple Allocation Hub Location Problem
Journal of Computational Interdisciplinary Sciences, 2013
The object of this work is to present an exact solution for the capacitated multiple allocation hub location problem. In order to accelerate the search for solutions, the Local Branching (LB) technique was employed. This technique is based on branch-and-cut methods and it also incorporates some ideas present in local search and metaheuristics.
The capacitated multiple allocation hub location problem: Formulations and algorithms
2000
In this paper we consider and present formulations and solution approaches for the capacitated multiple allocation hub location problem. We present a new mixed integer linear programming formulation for the problem. We also construct an ecient heuristic algorithm, using shortest paths. We incorporate the upper bound obtained from this heuristic in a linear-programming-based branch-and-bound solution procedure. We present the results of extensive computational experience with both the heuristic and the exact methods.
Solving the Hub location problem in telecommunication network design: A local search approach
Networks, 2004
This paper deals with a Hub Location Problem arising in Telecommunication Network Design. The considered network presents two different kinds of nodes: access nodes, that represent source and destination of traffic demands but cannot be directly connected, and transit nodes, that have no own traffic demand but collect traffic from access nodes and route it through the network. Transit nodes are supposed to be fully connected. Given a set of access nodes and a set of potential locations for the transit nodes, the problem is to decide number and positions of the transit nodes in order to guarantee that all access nodes are allocated to a transit node, satisfying capacity constraints. The goal is to minimize the total cost of the network, which is the sum of connection costs and nodes fixed costs. The problem is a Hub Location Problem, which is known to be NP-hard. A local search approach is proposed and different metaheuristic algorithms, such as tabu search, iterated local search and random multistart, have been developed, based on such local search 1 .
Operational Research, 2018
The hub location problem (HLP) concerns the location of hub nodes and allocation of other non-hub nodes to hubs in the network. Hubs are particular facilities that serve as mediators through the aggregation, consolidation, classification and distribution of network flows from origin to destination. Most models use constant penalty parameters to calculate the aggregation and distribution cost in the objective function. The selected parameter values can significantly affect the number of hubs and their locations in the network. Furthermore, most studies on HLP assume that network hubs are always operational but every established hub has the potential to fail during use. In this paper, we propose the capacitated modular single allocation hub location problem with possibilities of hub disruptions, whereby a low number of capacitated transportation vehicles is used instead of constant parameters. The problem is modeled as a two-stage stochastic program, and a metaheuristic algorithm based on the adaptive large neighbourhood search is proposed. The computational experiment results demonstrate the high efficiency of the proposed solution method.
Network hub location problems: The state of the art
European Journal of Operational Research, 2008
Hubs are special facilities that serve as switching, transshipment and sorting points in many-to-many distribution systems. The hub location problem is concerned with locating hub facilities and allocating demand nodes to hubs in order to route the traffic between origin-destination pairs. In this paper we classify and survey network hub location models. We also include some recent trends on hub location and provide a synthesis of the literature. inter-hub connections; and that no direct service (between two non-hub nodes) is allowed. Although these assumptions are relaxed in some studies, this paper assumes that these three assumptions are satisfied unless otherwise stated. This paper classifies and surveys network hub location models. In network hub location problems there is a given network with n nodes on which the set of origins, destinations and potential hub locations are identified. The flow between origin-destination pairs, an attribute of interest associated with flows on links in the network (cost, time, distance, etc.) and the hub-to-hub transportation discount factor a are known.
Single-assignment hub location problems with multiple capacity levels
Transportation Research Part B: Methodological, 2010
In this paper, an extension of the classical capacitated single-allocation hub location problem is studied in which the size of the hubs is part of the decision making process. For each potential hub a set of capacities is assumed to be available among which one can be chosen. Several formulations are proposed for the problem, which are compared in terms of the bound provided by the linear programming relaxation. Different sets of inequalities are proposed to enhance the models. Several preprocessing tests are also presented with the goal of reducing the size of the models for each particular instance. The results of the computational experiments performed using the proposed models are reported.