Some heuristic methods for solving p-median problems with a coverage constraint

Sáez-Aguado, Jesús; Trandafir, Paula Camelia

doi:10.1016/j.ejor.2012.02.011

Cited by 14 publications

(7 citation statements)

References 23 publications

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“…There are two through train services 1 → 3 and 1 → 4. In this case, 14 is directly shipped to the destination. While 15 is directly shipped to technical station 3, and 15 still needs to be reclassified at technical stations 3 and 4.…”

Section: An Example Of Wagon Flow Organization Problemmentioning

confidence: 99%

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Synthetic Optimization Model and Algorithm for Railway Freight Center Station Location and Wagon Flow Organization Problem

Liu

Song

et al. 2014

Mathematical Problems in Engineering

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The railway freight center stations location and wagon flow organization in railway transport are interconnected, and each of them is complicated in a large-scale rail network. In this paper, a two-stage method is proposed to optimize railway freight center stations location and wagon flow organization together. The location model is present with the objective to minimize the operation cost and fixed construction cost. Then, the second model of wagon flow organization is proposed to decide the optimal train service between different freight center stations. The location of the stations is the output of the first model. A heuristic algorithm that combined tabu search (TS) with adaptive clonal selection algorithm (ACSA) is proposed to solve those two models. The numerical results show the proposed solution method is effective. Literature ReviewThe location of railway freight center stations is similar to hub location problem, which is among the most critical management decisions. Many models have been proposed

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Section: An Example Of Wagon Flow Organization Problemmentioning

confidence: 99%

“…Batanović et al 's study [13] concerned the uncertain parameters in maximum covering location problem, which were modeled by fuzzy set. Sáez-Aguado and Trandafir [14] improved the p-median model by considering a coverage constraint. A dynamic uncapacitated hub location problem was present in Contreras et al 's paper [15].…”

mentioning

confidence: 99%

Synthetic Optimization Model and Algorithm for Railway Freight Center Station Location and Wagon Flow Organization Problem

Liu

Song

et al. 2014

Mathematical Problems in Engineering

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“…Among the various clustering models available, the p-median model has received significant attention across fields (e.g., Sáez-Aguado and Trandafir, 2012;Brusco et al, 2012;Avella et al, 2012). The p-median model aims to partition objects into clusters such that the sum of the distances from each object to the central exemplar of its cluster (i.e., median) is minimal.…”

Section: Introductionmentioning

confidence: 99%

A model for clustering data from heterogeneous dissimilarities

Santi

Aloise

Blanchard

2016

European Journal of Operational Research

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“…Recently, Racunica and Wynter [ 5 ] used two variable-reduction heuristics to solve the hub location problem in intermodal transport hub-and-spoke networks. Jesús and Paula [ 6 ] added a coverage constraint to the p -median model and applied three different algorithms to solve it.…”

Section: Introductionmentioning

confidence: 99%

Robust Optimization Model and Algorithm for Railway Freight Center Location Problem in Uncertain Environment

Liu

Song

et al. 2014

Computational Intelligence and Neuroscience

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Railway freight center location problem is an important issue in railway freight transport programming. This paper focuses on the railway freight center location problem in uncertain environment. Seeing that the expected value model ignores the negative influence of disadvantageous scenarios, a robust optimization model was proposed. The robust optimization model takes expected cost and deviation value of the scenarios as the objective. A cloud adaptive clonal selection algorithm (C-ACSA) was presented. It combines adaptive clonal selection algorithm with Cloud Model which can improve the convergence rate. Design of the code and progress of the algorithm were proposed. Result of the example demonstrates the model and algorithm are effective. Compared with the expected value cases, the amount of disadvantageous scenarios in robust model reduces from 163 to 21, which prove the result of robust model is more reliable.

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Some heuristic methods for solving p-median problems with a coverage constraint

Cited by 14 publications

References 23 publications

Synthetic Optimization Model and Algorithm for Railway Freight Center Station Location and Wagon Flow Organization Problem

Synthetic Optimization Model and Algorithm for Railway Freight Center Station Location and Wagon Flow Organization Problem

A model for clustering data from heterogeneous dissimilarities

Robust Optimization Model and Algorithm for Railway Freight Center Location Problem in Uncertain Environment

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