Abstract
Overally location problem could be classified as desirable facility location and undesirable facility location. In the undesirable facility location problem contrary to desirable location, facilities are located far from service receiver facilities as much as possible. The problem of locating such facilities ...
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Overally location problem could be classified as desirable facility location and undesirable facility location. In the undesirable facility location problem contrary to desirable location, facilities are located far from service receiver facilities as much as possible. The problem of locating such facilities is discussed in this paper. This research is focused on the “not in my backyard” (NIMBY) which refers to the social phenomena in which residents are opposed to locate undesirable facilities around their houses. Examples of such facilities include electric transmission lines and recycling centers. Due to the opposition typically encountered in constructing an undesirable facility, the facility planner should understand the nature of the NIMBY phenomena and consider it as a key factor in the determining facility location. A integer linear model of this problem and a Lagrange relaxation method are proposed in this research. This method relaxes up the hard constraints and adds the constraints to the objective function with a Lagrangian multiplier. To show that the Lagrangian relaxation method is computationally powerful exact solution algorithm and is capable to solve the medium-size problems, the performance of the proposed algorithm is examined by applying it to several test problems.
Alireza Alinajad; Samrand Salari; Azadeh Seif
Volume 10, Issue 26 , January 2012, , Pages 123-146
Abstract
This research investigates issues relating to facilities location whichcovers network design under the conditions of uncertainty and robuststate. In this direction a model is developed in which lack of certaintyis taken into consideration regarding parameters such as demand andvarious costs. Unlike the ...
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This research investigates issues relating to facilities location whichcovers network design under the conditions of uncertainty and robuststate. In this direction a model is developed in which lack of certaintyis taken into consideration regarding parameters such as demand andvarious costs. Unlike the classical methods that the structure ofnetwork is predefined and is predetermined, the facilities locationmakes decisions with respect to the structure of the network.The discussed issue in many real and actual applications such as roadsnetwork, communication systems and etc does exist and locating thefacilities and designing the main network simultaneously areconsidered as important factors; therefore redesigning andoptimization of models which look for simultaneous solutions seemessential. There have been various strategies in the literature ofuncertainty optimization. Two of the most important strategies are the“Probabilistic Optimization” and “Robust Optimization”.This article employs the robust optimization to resolve the uncertaintyand the modelization arguments. Moreover using random samples, thedeveloped model is validated and for further mathematical analysis isutilized
