The hierarchical hub maximal covering problem with determinate cover radiuses

Sahraeian, Rashed; Korani, Ehsan

doi:10.1109/ieem.2010.5674407

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…Yaman (2009) also studies a different version of this problem by considering service-level quality, proposing a mixed-integer programming model. Sahraeian and Korani (2010) consider the same threelevel hub network structure under a maximal covering objective. Finally, Alumur et al (2012b ) present a hierarchical multimodal hub location problem with time-definite deliveries.…”

Section: Related Literaturementioning

confidence: 99%

Routing and scheduling decisions in the hierarchical hub location problem

Dükkancı

Kara

2017

Computers & Operations Research

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a b s t r a c tHubs are facilities that consolidate and disseminate flow in many-to-many distribution systems. The hub location problem considers decisions that include the locations of hubs in a network and the allocations of demand (non-hub) nodes to these hubs. We propose a hierarchical multimodal hub network structure, and based on this network, we define a hub covering problem with a service time bound. The hierarchical network consists of three layers in which we consider a ring-star-star (RSS) network. This multimodal network may have different types of vehicles in each layer. For the proposed problem, we present and strengthen a mathematical model with some variable fixing rules and valid inequalities. Also, we develop a heuristic solution algorithm based on the subgradient approach to solve the problem in more reasonable times. We conduct the computational analysis over the Turkish network and the CAB data sets.

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Section: Related Literaturementioning

confidence: 99%

Routing and scheduling decisions in the hierarchical hub location problem

Dükkancı

Kara

2017

Computers & Operations Research

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“…(15) explains Sahraeian and Korani's (2010) approach for calculating the cover radius to apply it in the model. By using distance table, the minimum number in each column is obtained (without zero), these values denote vicinity to nodes.…”

Section: Computing the Cover Constraintmentioning

confidence: 99%

Differential evolution algorithm for multi-commodity and multi-level of service hub covering location problem

Eghbali-Zarch¹,

Abedzadeh²,

Setak³

2013

ijiec

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The hub location problem involves a network of origins and destinations over which transportation takes place. There are many studies associated with finding the location of hub nodes and the allocation of demand nodes to these located hub nodes to transfer the only one kind of commodity under one level of service. However, in this study, carrying different commodity types from origin to destination under various levels of services (e.g. price, punctuality, reliability or transit time) is studied. Quality of services experienced by users such as speed, convenience, comfort and security of transportation facilities and services is considered as the level of service. In each system, different kinds of commodities with various levels of services can be transmitted. The appropriate level of service that a commodity can be transmitted through is chosen by customer preferences and the specification of the commodity. So, a mixed integer programming formulation for single allocation hub covering location problem, which is based on the idea of transferring multi commodity flows under multi levels of service is presented. These two are applied concepts, multi-commodity and multi-level of service, which make the model's assumptions closer to the real world problems. In addition, a differential evolution algorithm is designed to find near-optimal solutions. The obtained solutions using differential evolution (DE) algorithm (upper bound), where its parameters are tuned by response surface methodology, are compared with exact solutions and computed lower bounds by linear relaxation technique to prove the efficiency of proposed DE algorithm.

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