Article history: Received 1 September 2013 Received in revised form 6 May 2014 Accepted 7 May 2014 Available online 20 May 2014

A large number of heuristic search algorithms are available for function optimization. Each of these heuristics, e.g., simulated annealing, genetic algorithms, tabu search, etc., has been shown to be effective at finding good solutions efficiently. However, little work has been directed at determining what are the important problem characteristics for which one algorithm is more efficient than ...

In this paper, we present a novel multi-objective mathematical model for capacitated single allocation hub location problem. There are the vehicle capacity constraint and capacity restrictions amount of the incoming flow to the hub while the balancing requirements of incoming quantities of flow to the each hub is considered. Moreover, there is a set of available capacities for each potential hu...

in this paper, a facility location problem of distribution systems, as one of the important and strategic issues in supply chain management, has been studied in a three-level supply chain under a stochastic condition. for this purpose, a two-stage mathematic model has been proposed for the location-allocation problem of distribution systems with regard to backup facilities for disrupting wareho...

in this paper, we present the stochastic version of maximal covering location problem which optimizes both location and allocation decisions, concurrently. it’s assumed that traveling time between customers and distribution centers (dcs) is uncertain and described by normal distribution function and if this time is less than coverage time, the customer can be allocated to dc. in classical model...

The aim of this study is to present a hybrid algorithm based on two meta-heuristic algorithms named Vibration Damping Optimization (VDO) algorithm and Genetic Algorithm (GA) for solving the stochastic capacitated location-allocation problem. For solving the model more efficiently, the simplex algorithm, stochastic simulation and the proposed hybrid algorithm are integrated to design a powerful ...

We study a strategic model in which a defender must allocate defensive resources to a collection of locations, and an attacker must choose a location to attack. The defender does not know the attacker's preferences, while the attacker observes the defender's resource allocation. The defender's problem gives rise to negative externalities, in the sense that increasing the resources allocated to ...

We study a strategic model in which a defender must allocate defensive resources to a collection of locations, and an attacker must choose a location to attack. The defender does not know the attacker's preferences, while the attacker observes the defender's resource allocation. The defender's problem gives rise to negative externalities, in the sense that increasing the resources allocated to ...