Hub facility location problem looks to find the most appropriate location for deploying such facilities. An important factor in such a problem is the pool of potential locations from which the optimal locations must be selected. The present research was performed to address two key objectives: identifying the factors contributing to the selection locations for hub establishment, and presenting ...

Jain et al. proposed two well-known algorithms for the Metric Facility Location Problem (MFLP), that achieve approximation ratios of 1.861 and 1.61. Mahdian et al. combined the latter algorithm with scaling and greedy augmentation techniques, obtaining a 1.52-approximation for the MFLP. We consider a generalization of the Squared Euclidean Facility Location Problem, when the distance function i...

assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. in this study, we solve quadratic assignment problem (qap), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. it should be noted that any facility must be assign to only one location. in this paper, first o...

In the maximum facility location problem, we are given a set of clients C and facilities F . Assigning a client u to a facility v incurs a cost w uv and each facility has an associated interval I v on the real line. Our goal is to assign as many clients to open facilities in order to maximise the cost of assignment, subject to the constraint that open facilities cannot have their respective int...

We present a deterministic kinetic data structure for the facility location problem that maintains a subset of the moving points as facilities such that, at any point of time, the accumulated cost for the whole point set is at most a constant factor larger than the current optimal cost. At any point of time, the cost that arise for a point depends on the status and the position of the point. In...

  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 mod...