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The k-level Uncapacitated Facility Location (UFL) problem is a generalization of the UFL and the k-median problems. A significant shortcoming of the classical UFL problem is that often a few very distant customers, known as outliers, can leave an undesirable effect on the final solution. This deficiency is considered in a new variant called UFL with outliers, in which, in contrast to the other problems that need all of the customers to be serviced, there is no need to service the entire set of customers. UFL with Penalties (UFLWP) is a variant of the UFL with outliers problem in which we will decide on whether to provide service for each customer and pay the connection cost, or to reject it... 

Disruptions rarely occur in supply chains, but their negative financial and technical impacts make the recovery process very slow. In this paper, we propose a capacitated supply chain network design (SCND) model under random disruptions both in facility and transportation, which seeks to determine the optimal location and types of distribution centers (DC) and also the best plan to assign customers to each opened DC. Unlike other studies in the extent literature, we use new concepts of reliability to model the strategic behavior of DCs and customers at the network: (1) Failure of DCs might be partial, i.e. a disrupted DC might still be able to serve with a portion of its initial capacity (2)... 

We study networks of facilities that must provide coverage under conditions of uncertainty with respect to travel times and customer demand. We model this uncertainty through a set of scenarios. Since opening new facilities and/or closing existing ones is often quite expensive, we focus on optimal re-configuration of the network, that is finding a facility set that achieves desired thresholds with respect to expected and minimal coverage, while retaining as many of the existing facilities as possible. We illustrate our model with an example of Toronto Fire Service. We demonstrate that relocating just a few facilities can have the same effect as opening a similar number of new ones. We... 

In this work, a bi-objective multi-facility location-allocation problem is investigated, in which the locations of the customers and their arrivals are stochastic. We first formulate the problem as a continuous location-allocation model with no constraints on the capacity of the facilities. Then, we develop an approximated discrete model in which the facilities with limited capacities can be located on a set of candidate points. The proposed model has two objective functions that are evaluated using discrete event system simulation. The first objective is to minimize the expected total time the customers spend in the system until their services begin. The time that each customer spends in... 

This paper examines the spoke and hub location decisions in a routing problem. To minimize the total cost, the study analyzes on how to locate the spokes, hubs and the allocation of spoke nodes to hub nodes, the routing among the nodes and the number of vehicles assigned to each hub thoroughly. As there might be no facility assigned to some points, unsatisfied demands must be distributed to other nodes with available facilities. Furthermore, the realized demand is determined by considering the perceived utility of each path, using The Gravity rule. For this purpose, the proposed nonlinear model is transformed into a linear programming model, where some tightening rules and preprocessing... 

In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand and immobile servers is studied. Two objectives considered in this problem are: (1) minimizing the average customer waiting time and (2) minimizing the average facility idletime percentage. We formulate this problem using queuing theory and solve the model by a genetic algorithm within the desirability function framework. Several examples are presented to demonstrate the applications of the proposed... 

A facility location problem deals with locating the best place for a group of facilities, among distinct demand points, minimizing a certain locational optimization function. In this paper, distributed, asynchronous, and scalable algorithms are presented for solving a facility location problem known as continuous n-median problem (generalized Fermat-Weber problem) via multi-agent robotic systems. The algorithms are discussed both in continuous and discrete time domain, and their validity is proved. It is also shown that the solution of this facility location problem is the set of points that are the geometric medians of their corresponding Voronoi cells  

In this paper, three fundamental properties of a potential field-based flocking algorithm, i.e. merging of neighbouring graphs during the system evolution, collision avoidance and convergence of position of the centre of mass of informed agents to that of virtual leader are discussed. Next, these properties are utilized to determine required number of informed agents based on initial position of uninformed ones and consequently reduce the domain of search in optimization problems defined for finding the optimal number of required informed agents. Finally, a new optimization framework is proposed, which benefits Voronoi diagrams in order to reduce the number of informed agents required for... 

Most of the publications regarding the maxim covering location problem (MCLP) address the case where the decision is to be made for one period. In this paper, we deal with a rather untouched version of MCLP which is called dynamic MCLP (DMCLP). In order to solve this problem, a simulated annealing (SA) has been presented. The proposed solution algorithm is capable of solving problems with up to 2500 demand nodes and 200 potential facilities with a fair amount of exactness. Our experiments showed that the proposed approach finds solutions with errors less than one percent  

This paper introduces a new consensus protocol whose features are different from known consensus protocols available in the literature. The relation between discrete coverage algorithms over a convex polygon for solving a facility location problem (n-median problem) along with some notions in agreement over acyclic digraphs have been used to establish a novel constrained consensus protocol. Its convergence for the special case of acyclic digraphs with switching topology is presented. Extension of the results for other graph topologies and communication links are left for future works. © 2009 IEEE  

This paper presents a model for “Domestic Facility and Hub Location” in transportation network. Number of hubs and facilities are unknown and the objective is to minimize the transportation cost, lost demand penalty and facility set up costs. Also the distribution of demand among domestic facilities and hubs adheres to gravity rule. To solve the problem, sequential and integrated approaches were undertaken. In the sequential approach, domestic facilities were allocated and hubs were selected afterwards. However the integrated approach deals with both concurrently, with a more sophisticated steps reaching to the solution. This is mainly because the demand itself is highly dependent to where... 

In this paper, we propose an optimization framework to retrieve an optimal group of experts to perform a multi-aspect task. While a diverse set of skills are needed to perform a multi-aspect task, the group of assigned experts should be able to collectively cover all these required skills. We consider three types of multi-aspect expert group formation problems and propose a unified framework to solve these problems accurately and efficiently. The first problem is concerned with finding the top k experts for a given task, while the required skills of the task are implicitly described. In the second problem, the required skills of the tasks are explicitly described using some keywords but each... 

In this research, a maximal covering location problem (MCLP) with real-world constraints such as multiple types of facilities and vehicles with different setup costs is taken into account. An original mixed integer linear programming (MILP) model is constructed in order to find the optimal solution. Since the problem at hand is shown to be NP-hard, a constructive heuristic method and a meta-heuristic approach based on genetic algorithm (GA) are developed to solve the problem. To find the most effective solution technique, a set of problems of different sizes is randomly generated and solved by the proposed solution methods. Computational results demonstrate that the heuristic method is... 

Many research works in mathematical modeling of the facility location problem have been carried out in discrete and continuous optimization area to obtain the optimum number of required facilities along with the relevant allocation processes. This paper proposes a new multi-objective facility-location problem within the batch arrival queuing framework. Three objective functions are considered: (I) minimizing the weighted sum of the waiting and the traveling times, (II) minimizing the maximum idle time pertinent to each facility, and (III) minimizing the total cost associated with the opened facilities. In this way, the best combination of the facilities is determined in the sense of... 

In this paper, a novel multi-objective location model within multi-server queuing framework is proposed, in which facilities behave as M/M/m queues. In the developed model of the problem, the constraints of selecting the nearest-facility along with the service level restriction are considered to bring the model closer to reality. Three objective functions are also considered including minimizing (I) sum of the aggregate travel and waiting times, (II) maximum idle time of all facilities, and (III) the budget required to cover the costs of establishing the selected facilities plus server staffing costs. Since the developed model of the problem is of an NP-hard type and inexact solutions are... 

In this paper, we propose an optimization framework to retrieve an optimal group of experts to perform a given multi-aspect task/project. Each task needs a diverse set of skills and the group of assigned experts should be able to collectively cover all required aspects of the task. We consider three types of multiaspect team formation problems and propose a unified framework to solve these problems accurately and efficiently. Our proposed framework is based on Facility Location Analysis (FLA) which is a well known branch of the Operation Research (OR). Our experiments on a real dataset show significant improvement in comparison with the state-of-the art approaches for the team formation... 

We propose modified hybridizations of genetic algorithms with some neighborhood search based metaheuristics. In our hybrid algorithms, we consider gradually increasing probability for the application of the neighborhood search procedure on the best individuals as the number of iterations of the genetic algorithm increases. We implement the proposed hybrid algorithms and compare their performance with two other recently proposed hybrid algorithms which, in contrast, use the neighborhood search procedure on all the individuals of the population, two hybrid algorithms applying simulated annealing on the best individual in the papulation in every iteration and three non-hybrid metaheuristic... 

The rising disruptions of interdictors force supply chains’ designers to embody the protection decisions when locating the facilities. In the presence of variability in the intensity of disruptions, a risk measure is incorporated into the decision-making. The designer-interdictor bi-level problem, therefore, optimizes the joint location and protection decisions with respect to the conditional value-at-risk. This configuration has been absent from the literature. An accelerated modified Benders decomposition algorithm is developed and enhanced by being hybridized with a sample average approximation-based genetic algorithm. We examine how this new configuration influences the optimal solutions... 

This paper addresses a bi-level mixed-integer nonlinear programming (MINLP) model for the competitive facility location problem in a closed-loop supply chain (CLSC), in which a firm (i.e., leader) aims at entering a market by locating new distribution and collection facilities, where a competitor (i.e., follower) already exists. The goal is to find the location and attractiveness of each facility going to be established by the leader who seeks to maximize its profit while also taking the follower's response into account. The attractiveness of each facility is a function of integer variables related to the facility's characteristics. Customer behavior is considered to be probabilistic based...