89 research outputs found

    Locating emergency services with priority rules: The priority queuing covering location problem

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    One of the assumptions of the Capacitated Facility Location Problem (CFLP) is that demand is known and fixed. Most often, this is not the case when managers take some strategic decisions such as locating facilities and assigning demand points to those facilities. In this paper we consider demand as stochastic and we model each of the facilities as an independent queue. Stochastic models of manufacturing systems and deterministic location models are put together in order to obtain a formula for the backlogging probability at a potential facility location. Several solution techniques have been proposed to solve the CFLP. One of the most recently proposed heuristics, a Reactive Greedy Adaptive Search Procedure, is implemented in order to solve the model formulated. We present some computational experiments in order to evaluate the heuristics’ performance and to illustrate the use of this new formulation for the CFLP. The paper finishes with a simple simulation exercise.Location, queuing, greedy heuristics, simulation

    Modeling and analysis of the generalized warehouse location problem with staircase costs

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    The Capacitated Warehouse Location consists of determining the number and locations of capacitated warehouses on a set of potential sites such that demands of predefined customers are met. Two typical assumptions in modeling this problem are: the capacity of warehouses is constant and that warehouses are able to truly satisfy customer demands. However, while these kinds of assumptions define a well structured problem from the mathematical modeling perspective, they are not realistic. In this thesis we relaxed such constraints based on the fact that warehouses can be built in various sizes and also warehouses can put in orders for unsatisfied customers' demand directly to the manufacturing plant with additional costs. This flexibility can lead to best decision making ability for managers and supply chain specialists to decide between higher capacity level with higher fixed and variable costs at the warehouse or direct ordering from the manufacturing plant. A new non linear integer programming formulation with staircase costs for multiple commodities in supply chain network is presented, and new method for linearizing the model is described. Computational results indicate that reasonably good solution can be obtained by the proposed linear model. Also for solving larger problems we developed a Tabu Search algorithm. The comparisons of the result between nonlinear/linear model and the Tabu Search algorithm are also presented

    Mathematical Model and Stochastic Multi-Criteria Acceptability Analysis for Facility Location Problem

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    This paper studies a real-life public sector facility location problem. The problem fundamentally originated from the idea of downsizing the number of service centres. However, opening of new facilities is also considered in case the current facilities fail to fulfil general management demands. Two operation research methodologies are used to solve the problem and the obtained results are compared. First, a mathematical programming model is introduced to determine where the new facilities will be located, and which districts get service from which facilities, as if there were currently no existing facilities. Second, the Stochastic Multi-criteria Acceptability Analysis-TRI (SMAA-TRI) method is used to select the best suitable places for service centres among the existing facilities. It is noted that the application of mathematical programming model and SMAA-TRI integration approach on facility location problem is the first study in literature. Compression of outcomes shows that mixed integer linear programming (MILP) model tries to open facilities in districts which are favoured by SMAA-TRI solution.</span

    Mathematical Model and Stochastic Multi-Criteria Acceptability Analysis for Facility Location Problem

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    This paper studies a real-life public sector facility location problem. The problem fundamentally originated from the idea of downsizing the number of service centres. However, opening of new facilities is also considered in case the current facilities fail to fulfil general management demands. Two operation research methodologies are used to solve the problem and the obtained results are compared. First, a mathematical programming model is introduced to determine where the new facilities will be located, and which districts get service from which facilities, as if there were currently no existing facilities. Second, the Stochastic Multi-criteria Acceptability Analysis-TRI (SMAA-TRI) method is used to select the best suitable places for service centres among the existing facilities. It is noted that the application of mathematical programming model and SMAA-TRI integration approach on facility location problem is the first study in literature. Compression of outcomes shows that mixed integer linear programming (MILP) model tries to open facilities in districts which are favoured by SMAA-TRI solution.</span

    Location models in the public sector

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    The past four decades have witnessed an explosive growth in the field of networkbased facility location modeling. This is not at all surprising since location policy is one of the most profitable areas of applied systems analysis in regional science and ample theoretical and applied challenges are offered. Location-allocation models seek the location of facilities and/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or several objectives generally related to the efficiency of the system or to the allocation of resources. This paper concerns the location of facilities or services in discrete space or networks, that are related to the public sector, such as emergency services (ambulances, fire stations, and police units), school systems and postal facilities. The paper is structured as follows: first, we will focus on public facility location models that use some type of coverage criterion, with special emphasis in emergency services. The second section will examine models based on the P-Median problem and some of the issues faced by planners when implementing this formulation in real world locational decisions. Finally, the last section will examine new trends in public sector facility location modeling.Location analysis, public facilities, covering models

    Optimisation of an integrated transport and distribution system

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    Imperial Users onl

    Solution Methods for the \u3cem\u3ep\u3c/em\u3e-Median Problem: An Annotated Bibliography

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    The p-median problem is a graph theory problem that was originally designed for, and has been extensively applied to, facility location. In this bibliography, we summarize the literature on solution methods for the uncapacitated and capacitated p-median problem on a graph or network

    A Simulated Annealing Algorithm within the Variable Neighbourhood Search Framework to Solve the Capacitated Facility Location-Allocation Problem

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    In this study, we discuss the capacitated facility location-allocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. In this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. To tackle the problem efficiently and effectively, an efficient hybrid solution algorithm based on several meta-heuristics and an exact algorithm is put forward. This algorithm generates neighborhoodsby combining the main concepts of variable neighborhood search, simulated annealing, and tabu search and finds the local optima by using an algorithm that uses an exact method in its framework. Finally, to test the algorithms’ performance, we apply numerical experiments on both randomly generated and standard test problems. Computational experiments show that our algorithm is more effective and efficient in term of CPU time and solutions quality in comparison with CPLEX solver
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