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

2016 ◽  
Vol 28 (3) ◽  
pp. 245-256 ◽  
Author(s):  
Selahattin Karabay ◽  
Erkan Köse ◽  
Mehmet Kabak ◽  
Eren Ozceylan
Keyword(s):  
Mathematical Programming ◽  
Facility Location ◽  
Location Problem ◽  
Programming Model ◽  
Real Life ◽  
Facility Location Problem ◽  
Mixed Integer ◽  
Mathematical Programming Model ◽  
General Management ◽  
New Facilities

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.

scholarly journals Mathematical Programming Model for the Two-Level Facility Location Problem: The Case of Tanzanian Emergence Maize Distribution Network for 2004–2010 Maize Data

2021 ◽  
Vol 47 (3) ◽  
pp. 1020-1032
Author(s):  
Said A Sima
Keyword(s):  
Mathematical Programming ◽  
Facility Location ◽  
Location Problem ◽  
Programming Model ◽  
Transportation Network ◽  
Distribution Network ◽  
Facility Location Problem ◽  
Optimal Location ◽  
Mathematical Programming Model ◽  
Maize Crop

A two-level facility location problem (FLP) has been studied in the transportation network of emergence maize crop in Tanzania. The facility location problem is defined as the optimal location of facilities or resources so as to minimize costs in terms of money, time, distance and risks with the relation to supply and demand points. Distribution network design problems consist of determining the best way to transfer goods from the supply to the demand points by choosing the structure of the network such that the overall cost is minimized. The three layers, namely production centres (PCs), distribution centres (DCs) and customer points (CPs) are considered in the two-level FLP. The flow of maize from PCs to CPs through DCs is designed at a minimum cost under deterministic mathematical programming model. The four decisions to be made simultaneously are: to determine the locations of DCs (including number of DCs), allocation of CPs to the selected DCs, allocation of selected DCs to PCs, and to determine the amount of maize crop transported from PCs to DCs and then from DCs to CPs. The modelled problem generated results through optimization with respect to optimal location-allocation strategies. The results of the optimized network shows the improvement in costs saving compared to the manually operated existing network. The results show the costs saving of up to 18% which is equivalent to $2,910 thousand (TZS 2.9 billion). Keywords:    Optimization; Maize crop; Transportation network; Deterministic model; Facility location

scholarly journals Optimization of Empty Container Repositioning in Liner Shipping

2020 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Hüseyin Gençer ◽  
M. Hulusi Demir
Keyword(s):  
Mathematical Programming ◽  
Deterministic Model ◽  
Programming Model ◽  
Real Life ◽  
Real Data ◽  
Mixed Integer ◽  
Computational Time ◽  
Mathematical Programming Model ◽  
Empty Container ◽  
Empty Container Repositioning

Empty container repositioning (ECR), which arises due to imbalances in world trade, causes extra costs for the container liner carrier companies. Therefore, one of the main objectives of all liner carriers is to reduce ECR costs. Since ECR decisions involve too many parameters, constraints and variables, the plans based on real-life experiences cannot be effective and are very costly. For this purpose, this study introduces two mathematical programming models in order to make ECR plans faster, more efficient and at the lowest cost. The first mathematical programming model developed in this study is a mixed-integer linear programming (MILP) model and the second mathematical programming model is a scenario-based stochastic programming (SP) model, which minimize the total ECR costs. Unlike the deterministic model, the SP model takes into account the uncertainty in container demand. Both models have been tested with real data taken from a liner carrier company. The numerical results showed that, in a reasonable computational time, both models provide better results than real-life applications of the liner carrier company.

Lagrangian Bounds and a Heuristic for the Two-Stage Capacitated Facility Location Problem

2012 ◽  
Vol 1 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Igor Litvinchev ◽  
Edith L. Ozuna
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Computational Study ◽  
Facility Location Problem ◽  
Mixed Integer ◽  
Variable Cost ◽  
Fixed Cost ◽  
Two Stage ◽  
Capacitated Facility Location Problem ◽  
Capacitated Facility Location

In the two-stage capacitated facility location problem, a single product is produced at some plants in order to satisfy customer demands. The product is transported from these plants to some depots and then to the customers. The capacities of the plants and depots are limited. The aim is to select cost minimizing locations from a set of potential plants and depots. This cost includes fixed cost associated with opening plants and depots, and variable cost associated with both transportation stages. In this work, two different mixed integer linear programming formulations are considered for the problem. Several Lagrangian relaxations are analyzed and compared, and a Lagrangian heuristic producing feasible solutions is presented. The results of a computational study are reported.

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