<p>Line location problem is a branch of facility location problems where the new facility aimed to be positioned with respect to the demand points, is a straight line. Let a set of demand points with negative and positive weights be given in the plane, where the negative/positive weight represents the undesirable/desirable interaction between the line and the demand points, respectively. This paper considers both desirable and undesirable aforementioned interactions simultaneously and provides bi-objective models for the semi-desirable line facility location problem for the first time by using Euclidean and rectilinear norms. In these models, the first objective function aims to locate the line as close to all demand points as possible to optimize the total transportation costs, while the second objective function minimizes the negative environmental interactions (such as noise and pollution, etc.) between part of demand points and the line. Then, we apply <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\:ϵ\)</EquationSource> </InlineEquation>-constraint method for tackling small-sized instances to validate the presented models. Next, two well-known evolutionary algorithms namely Multi-Objective Particle Swarm Optimization (MOPSO) and Non-dominates Sorting Genetic Algorithm-II (NSGA-II) are devised to solve large-sized instances. Moreover, four criteria and a statistical procedure are applied to compare results obtained by MOPSO and NSGA-II.</p>

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Bi-objective location of a semi-desirable line facility and evolutionary solution algorithms

  • Mehdi Golpayegani,
  • Jafar Fathali,
  • Haleh Moradi

摘要

Line location problem is a branch of facility location problems where the new facility aimed to be positioned with respect to the demand points, is a straight line. Let a set of demand points with negative and positive weights be given in the plane, where the negative/positive weight represents the undesirable/desirable interaction between the line and the demand points, respectively. This paper considers both desirable and undesirable aforementioned interactions simultaneously and provides bi-objective models for the semi-desirable line facility location problem for the first time by using Euclidean and rectilinear norms. In these models, the first objective function aims to locate the line as close to all demand points as possible to optimize the total transportation costs, while the second objective function minimizes the negative environmental interactions (such as noise and pollution, etc.) between part of demand points and the line. Then, we apply \(\:ϵ\) -constraint method for tackling small-sized instances to validate the presented models. Next, two well-known evolutionary algorithms namely Multi-Objective Particle Swarm Optimization (MOPSO) and Non-dominates Sorting Genetic Algorithm-II (NSGA-II) are devised to solve large-sized instances. Moreover, four criteria and a statistical procedure are applied to compare results obtained by MOPSO and NSGA-II.