A Bi-objective Credibility-based Fuzzy Mathematical Programming Model for a Healthcare Facility Location-network Design Problem

Author(s):  
R. Tavakkoli-Moghaddam ◽  
Pooya Pourreza ◽  
A. Bozorgi-Amiri ◽  
Nastaran Oladzad
2017 ◽  
Vol 34 (05) ◽  
pp. 1750026 ◽  
Author(s):  
Yuxiang Yang ◽  
Zuqing Huang ◽  
Qiang Patrick Qiang ◽  
Gengui Zhou

A firm sets up his facilities including manufacturing/remanufacturing plants and distribution/collection centers, incorporating an existing closed-loop supply chain (CLSC) network. The entering firm has to compete with the existing firms in the existing network. The entering firm behaves as the leader of a Stackelberg game while the existing firms in the existing network are followers. We assume that the entering firm can anticipate the existing firms’ reaction to his potential location decision before choosing his optimal policy. We use a CLSC network equilibrium model in which the decision makers are faced with multiple objectives to capture the existing firms’ reaction. A mathematical programming model with equilibrium constraints is developed for this competitive CLSC network design problem by taking into account the market competition existing in the decentralized CLSC network. A solution method is developed by integrating Genetic algorithm with an inexact logarithmic-quadratic proximal augmented Lagrangian method. Finally, numerical examples and the related results are studied for illustration purpose.


2014 ◽  
Vol 13 (01) ◽  
pp. 101-135 ◽  
Author(s):  
MUKESH KUMAR MEHLAWAT ◽  
PANKAJ GUPTA

In this paper, we develop a hybrid bi-objective credibility-based fuzzy mathematical programming model for portfolio selection under fuzzy environment. To deal with imprecise parameters, we use a hybrid credibility-based approach that combines the expected value and chance constrained programming techniques. The model simultaneously maximizes the portfolio return and minimizes the portfolio risk. We also consider an additional important criterion, namely, portfolio liquidity as a constraint in the model to make it better suited for practical applications. The proposed fuzzy optimization model is solved using a two-phase approach. An empirical study is included to demonstrate applicability of the proposed model and the solution approach in real-world applications of portfolio selection.


Author(s):  
Jun Zhao ◽  
Lixiang Huang

The management of hazardous wastes in regions is required to design a multi-echelon network with multiple facilities including recycling, treatment and disposal centers servicing the transportation, recycling, treatment and disposal procedures of hazardous wastes and waste residues. The multi-period network design problem within is to determine the location of waste facilities and allocation/transportation of wastes/residues in each period during the planning horizon, such that the total cost and total risk in the location and transportation procedures are minimized. With consideration of the life cycle capacity of disposal centers, we formulate the problem as a bi-objective mixed integer linear programming model in which a unified modeling strategy is designed to describe the closing of existing waste facilities and the opening of new waste facilities. By exploiting the characteristics of the proposed model, an augmented ε -constraint algorithm is developed to solve the model and find highly qualified representative non-dominated solutions. Finally, computational results of a realistic case demonstrate that our algorithm can identify obviously distinct and uniformly distributed representative non-dominated solutions within reasonable time, revealing the trade-off between the total cost and total risk objectives efficiently. Meanwhile, the multi-period network design optimization is superior to the single-period optimization in terms of the objective quality.


2014 ◽  
Vol 1030-1032 ◽  
pp. 2065-2068
Author(s):  
Xin Yuan Chen ◽  
Zhi Yuan Liu ◽  
Wei Deng

The paper addresses a park and ride network design problem in a bi-model transport network in a multi-objective decision making framework. A goal programming approach is adopted to solve the multi-objective park and ride network design problem. The goal programming approach considers the user-defined goals and priority structure, which are (i) traffic-efficient goal, (ii) total transit usage goal, (iii) spatial equity goal. This problem is formulated as a bi-level programming model. The upper level programming leads to minimize the deviation from stated goals in the context of a given priority ranking. While the lower level programming model is a modal split/traffic assignment model which is used to assess any given park and ride scheme. A heuristic tabu search algorithm is then adopted to solve this model.


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