Hub covering location problems with different coverage types

Karimi, Hossein; Bashiri, Mahdi

doi:10.1016/j.scient.2011.09.018

Cited by 64 publications

(38 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…He played a major role in completing hub modeling; minimum value ow on any spoke/hub connection problems, hub location problems with capacity limitation, Phub center location problems, hub covering location problems, and hub maximal covering location problems are some of his outstanding formulations. Karimi and Bashiri [9] considered several coverage requirements in a hub covering location model and also proposed two heuristic methods to solve it.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-objective Fuzzy Goal Programming P-hub Location and Protection Model with Back-up Hubs Considering Hubs Establishment Fixed Costs

2016

View full text Add to dashboard Cite

Abstract. The critical and undeniable role of hubs in telecommunication and networking brings about some precautions to be taken to protect networks against any disruption. In this paper, a multi-objective model in a group of hub location problems, referred to as protection models for survivable network design, is developed. In fact, this model is a hub location problem that aims to maximize the potential ow between the origin and destination node pairs in the network, which has the minimum potential ow among all O-D pairs, including multiple assignment and back-up routes. In addition, it concerns the xed cost of installation of the hub facilities. A fuzzy goal programming method is applied to solve the model. Di erent scenarios are implemented using Turkish data set and also numerical experiments are presented to illustrate the advantages of the proposed model in some aspects, compared to previous models. The results can give useful insights into telecommunication network design.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A Multi-objective Fuzzy Goal Programming P-hub Location and Protection Model with Back-up Hubs Considering Hubs Establishment Fixed Costs

2016

View full text Add to dashboard Cite

show abstract

“…To the best of our knowledge, there are two distinct formulations for HMCPs presented in Campbell (1994) and Karimi and Bashiri (2011). The proposed non-linear model consists of n 2 variables and n 4 þ n 2 þ n þ 1 constraints and the linearized version has 2n 2 binary variables and n 4 þ 2n 2 þ n þ 1 constraints.…”

Section: Location Of Demand Nodesmentioning

confidence: 99%

“…This formulation for multiple allocation HMCPs has 2n 2 binary variables and n 4 þ 3n 2 þ 1 constraints. Whereas the formulation proposed by Campbell (1994) has n 4 þ n 2 þ n variables with 2n 4 þ 1 constraints and the model proposed by Karimi and Bashiri (2011) has 2n 2 þ n variables with n 4 þ 2n 2 þ n þ 1 constraints (using the same coverage type).…”

Section: Multiple Allocation Hmcp Modelmentioning

confidence: 99%

See 1 more Smart Citation

A modified NSGA-II solution for a new multi-objective hub maximal covering problem under uncertain shipments

2014

View full text Add to dashboard Cite

Hubs are centers for collection, rearrangement, and redistribution of commodities in transportation networks. In this paper, non-linear multi-objective formulations for single and multiple allocation hub maximal covering problems as well as the linearized versions are proposed. The formulations substantially mitigate complexity of the existing models due to the fewer number of constraints and variables. Also, uncertain shipments are studied in the context of hub maximal covering problems. In many real-world applications, any link on the path from origin to destination may fail to work due to disruption. Therefore, in the proposed bi-objective model, maximizing safety of the weakest path in the network is considered as the second objective together with the traditional maximum coverage goal. Furthermore, to solve the bi-objective model, a modified version of NSGA-II with a new dynamic immigration operator is developed in which the accurate number of immigrants depends on the results of the other two common NSGA-II operators, i.e. mutation and crossover. Besides validating proposed models, computational results confirm a better performance of modified NSGA-II versus traditional one.

show abstract

“…Mohammadi et al (2011a) studied the location model for hub covering problem behaving as M/M/C queues and presented a nonlinear formulation and proposed an improved imperialist competitive algorithm to solve the model. Karimi and Bashiri (2011) studied hub covering problem with different coverage types over complete hub networks and proposed two heuristic procedures. Zarandi et al (2012) studied the multiple allocation hub set-covering problem considering the backup coverage and mandatory dispersion of hubs.…”

Section: Hub Location Problem (Hlp) Is Introduced Bymentioning

confidence: 99%

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

Eghbali-Zarch¹,

Abedzadeh²,

Setak³

2013

ijiec

View full text Add to dashboard Cite

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.

show abstract

Hub covering location problems with different coverage types

Cited by 64 publications

References 12 publications

A Multi-objective Fuzzy Goal Programming P-hub Location and Protection Model with Back-up Hubs Considering Hubs Establishment Fixed Costs

A Multi-objective Fuzzy Goal Programming P-hub Location and Protection Model with Back-up Hubs Considering Hubs Establishment Fixed Costs

A modified NSGA-II solution for a new multi-objective hub maximal covering problem under uncertain shipments

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

Contact Info

Product

Resources

About