نتایج جستجو برای: covering location allocation problem
تعداد نتایج: 1187700 فیلتر نتایج به سال:
The hub location problem deals with finding the location of hub facilities and allocating the demand nodes to these hub facilities so as to effectively route the demand between any origin–destination pair. In the extensive literature on this challenging network design problem, it has widely been assumed that the subgraph induced by the hub nodes is complete. Relaxation of this basic assumption ...
Abstract The purpose of this study is to consider an international facility location problem under uncertainty and present an integrated model for strategic and operational planning. The paper offers two methodologies for the location selection decision. First the extended VIKOR method for decision making problem with interval numbers is presented as a methodology for strategic evaluation of po...
This paper provides a framework in order to incorporate reliability issue as a sign of disruption in distribution systems and partial covering theory as a response to limitation in coverage radios and economical preferences, simultaneously into the traditional literatures of capacitated facility location problems. As a result we develop a bi-objective model based on the discrete scenarios for e...
This study extends a mathematical model that integrates the location, allocation, inventory replenishment and routing decisions simultaneously. To cope with inherent uncertainty of parameters, we implement a continuous-time Markov process and derive the performance measures of the system. Using the obtained results, the problem is formulated as a mixed integer nonlinear programing model (MINLP)...
This paper developed a mathematical model framework using the single allocation strategy for hub covering location problem. The model encompassed the transportation time covering under gradual decay function. Within a certain transportation time for the origin and destination nodes among two hubs, the route is fully covered, and beyond another specified transportation time the route is not cove...
The Constructive Genetic Algorithm (CGA) was proposed by Lorena and Furtado [6], as an alternative to the traditional GAs approach. Particularly the CGA directly evaluates schemata, works with a dynamic population size, performs mutation in complete structures, and uses heuristics in schemata and/or structure representation. The schemata are evaluated and can be added to the population if they ...
A 2-level hierarchical extension of the maximal covering location problem is considered and an e0ective method for its solution developed. A combined Lagrangean–surrogate (L–S) relaxation is de6ned which reduces to a 0–1 knapsack problem. Tests were carried out using a subgradient-based heuristic incorporating the L–S relaxation, with the resulting knapsack problems being solved both with and w...
Operation Timbang (OPT) Plus is one of the Philippines’ programs that focuses on nutrition by conducting an annual assessment for 0-59 months old children in barangays to identify malnutrition data area. The barangay smallest administrative entity Philippines. OPT a plan action estimates number individuals and identifies those who will get prioritized community. Iloilo City Health Office conduc...
This paper proposes a cluster partitioning technique to calculate improved upper bounds to the optimal solution of maximal covering location problems. Given a covering distance, a graph is built considering as vertices the potential facility locations, and with an edge connecting each pair of facilities that attend a same client. Coupling constraints, corresponding to some edges of this graph, ...
In this paper we develop a network location model that combines the characteristics of ordered median and gradual cover models resulting in the Ordered Gradual Covering Location Problem (OGCLP). The Gradual Cover Location Problem (GCLP) was specifically designed to extend the basic cover objective to capture sensitivity with respect to absolute travel distance. Ordered Median Location problems ...
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