نتایج جستجو برای: maximal covering location problems

تعداد نتایج: 924016  

Journal: :Eur. J. Comb. 2003
Weidong Gao Alfred Geroldinger

Let G be a finite Abelian group and D(G) its Davenport constant, which is defined as the maximal length of a minimal zero-sum sequence in G. We show that various problems on zero-sum sequences in G may be interpreted as certain covering problems. Using this approach we study the Davenport constant of groups of the form (Z/nZ)r , with n ≥ 2 and r ∈ N. For elementary p-groups G, we derive a resul...

2005
Retsef Levi Joseph Geunes H. Edwin Romeijn David B. Shmoys

We consider important generalizations of a wide class of traditional deterministic inventory and facility location models that we call inventory/facility location models with market selection. Instead of the traditional setting, we are given a set of markets, each specified by a sequence of demands and associated with a revenue. Decisions are made in two stages. We first make a decision of what...

2014
Rafael Blanquero Emilio Carrizosa Boglárka G.-Tóth

Covering problems are well studied in the Operations Research literature under the assumption that both the set of users and the set of potential facilities are finite. In this paper we address the following variant, which leads to a Mixed Integer Nonlinear Program (MINLP): locations of p facilities are sought along the edges of a network so that the expected demand covered is maximized, where ...

The main objective of facilities location and service system design is covering of potential customers’ demand. Many location models are extended with the covering objective and considered constraints, details of problem and its different aspects. In this paper the maximal covering location-allocation model for congested system is extended in the competitive environment. In the proposed model, ...

F. Moeen Moghadas

We consider the queueing maximal covering location-allocation problem (QM-CLAP) with an M/M/1 queueing system. We propose a new solution procedure based on decomposition of the problem into smaller sub-problems. We solve the resulting sub-problems both with a branch and bound algorithm and with the meta-heuristic GRASP. We also solve the entire model with GRASP. Computational results for these ...

Journal: :Operations Research Letters 2017

Journal: :European Journal of Operational Research 2020

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