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...

abstract one of the basic assumptions in hub covering problems is considering the covering radius as an exogenous parameter which cannot be controlled by the decision maker. practically and in many real world cases with a negligible increase in costs, to increase the covering radii, it is possible to save the costs of establishing additional hub nodes. change in problem parameters during the pl...

The Maximal Covering Location Problem (MCLP) maximizes the population that has a facility within a maximum travel distance or time. Numerous extensions have been proposed to enhance its applicability, like the probabilistic model for the maximum covering locationallocation with constraint in waiting time or queue length for congested systems, with one or more servers per service center. This pa...

This paper presents a simple, efficient algorithm to compute the covering graph of the lattice generated by a family B of subsets of a set X. The implementation of this algorithm has O((|X| + |B|) · |B|) time complexity per lattice element. This improves previous algorithms of Bordat (1986), Ganter and Kuznetsov (1998) and Jard et al. (1994). This algorithm can be used to compute the Galois (co...

In this paper, we study the restriction of an irreducible unitary representation π of the universal covering S̃p2n(R) to a Heisenberg maximal parabolic group P̃ . We prove that if π|P̃ is irreducible, then π must be a highest weight module or a lowest weight module. This is in sharp constrast with the GLn(R) case. In addition, we show that for a unitary highest or lowest weight module, π|P̃ decompo...