Multiple objective multiple allocation hub location problem

Mirzaei, Masoud; Bashiri, Mahdi

doi:10.1109/iccie.2010.5668249

Cited by 5 publications

(5 citation statements)

References 19 publications

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“…Hao et al [45] presented a method based on multi-objective optimization to determine the location of the hubs in a road passenger transportation plan. Mirzaei and Bashiri [46] used a multi-objective approach for hub location in order to reduce the overall cost of the networks minimizing the maximum travel time between the nodes. Köksalan and Soylu [47] presented two bi-criteria uncapacitated, multiple allocation p-hub location problems.…”

Section: Multi-objective Hub Location Allocationmentioning

confidence: 99%

Robust and fuzzy goal programming optimization approaches for a novel multi-objective hub location-allocation problem: A supply chain overview

Ghodratnama

Tavakkoli–Moghaddam

Azaron

2015

Applied Soft Computing

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Section: Multi-objective Hub Location Allocationmentioning

confidence: 99%

Robust and fuzzy goal programming optimization approaches for a novel multi-objective hub location-allocation problem: A supply chain overview

Ghodratnama

Tavakkoli–Moghaddam

Azaron

2015

Applied Soft Computing

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“…Tese objectives can account for customer satisfaction in designing HS networks. As Table 2 shows, fve diferent types of objectives have been explored in the literature, minimizing the total service time in hubs [27,30,33,35,37], minimizing the maximum service time in hubs [27,34,37], minimizing the maximum travel time between origin and destination (OD) pairs [28,31,32,38], minimizing the total travel time between OD pairs [29], and minimizing the total number of intermediate stops [12]. Table 2 outlines the objectives of the previous studies.…”

Section: Multiobjective Hlp Tis Section Reviews Multiobjectivementioning

confidence: 99%

Designing Airline Hub-and-Spoke Network and Fleet Size by a Biobjective Model Based on Passenger Preferences and Value of Time

Nasrollahi

Kordani

2023

Journal of Advanced Transportation

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This study presents a biobjective hub-and-spoke (HS) network design model for the global air passenger networks. The model explores the tradeoff between the total airline cost (airline preference) and lost time cost for passengers (user preference) as the model’s objectives. Most previous studies have focused on airline objectives and established HS networks based on the viewpoint of airlines, despite the importance of passenger objectives. Poor passenger service and inconvenience and dissatisfaction may lead to network breakdown. The major criteria for passenger dissatisfaction in HS networks are schedule and trip delays caused by nondirect flights. These delays (the lost time cost for passengers) are multiplied by the passengers’ value of time (VOT) and minimized as one of the model’s objectives. Another objective that is minimized is the transportation costs of the airline depending on the services provided (short-, medium-, and large-haul flights). The model is solved in a case study (Iranian Aeronautics Network) that is applied to the well-known yearbook of tourism statistics data. Pareto frontier was found for all candidate airports. Also, the number of aircraft required (short-, medium-, and large-haul), as well as the average load factor for different types of aircraft in various weights of the first objective (airline costs), was presented. The results of Pareto frontier indicated that Imam Khomeini International Airport should be selected as the global hub airport for Iran international flight network. Otherwise, Shiraz International Airport and Tabriz International Airport (as the first alternative), as well as Isfahan International Airport and Mashhad International Airport (as the second alternative), would be the best choices. The weight of the first objective (airline costs) seems to be between 0.7 to 1, a practical and logical weight that can reduce passenger costs (as the second objective) by 20% on average by adding only 15 long-haul, 40 medium-haul, and 37 short-haul aircraft to the airline’s fleet. Also, in this range, the average load factor for medium- and long-haul aircrafts is greater than 0.9, which seems to be ideal.

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“…In a recent study [20], Mirzaei and Bashiri present a model for multi-objective multiple allocation hub location problem. However, in their model, the hub network is assumed to be fully interconnected and no experimental result is given in the corresponding paper.…”

Section: Related Workmentioning

confidence: 99%

“…• Minimization of maximum travel time [20] • Minimization of environmental impacts like energy cost, noise, congestion, pollution, greenhouse gas emission [13] • Minimization of total transportation costs [21], [22], [29] • Minimization of the maximum delay at each hub [21] • Minimization of total time for processing the flow collected by the hubs [22] • Minimization of the sum of waiting times [29] • Minimization of total gas emissions [22], [29] • Maximization of benefits of transportation and establishment of the hub facilities [24] • Minimization of the total transportation time [24] • Maximization of the total amount of flow delivered in a predefined time [25] Costa et al [22] present two different mathematical models for a bi-objective capacitated single allocation HLP. In the first model, it is aimed to minimize the total costs and to minimize the total time for processing the flow collected by the hubs.…”

Section: Related Workmentioning

confidence: 99%

“…In the other problem, the objectives are minimizing the total transportation costs and minimizing the maximum delay at each hub. Mirzaei and Bashiri [20] consider a multi-objective approach for HLP to minimize the total cost and to minimize the maximum traveling time between nodes in the network. Ghodratnama et al [23] formulate a capacitated single allocation HLP with three objectives which are minimization of total costs including the transportation and installation, minimizing the sum of service time in the hubs, and minimization of total greenhouse emission.…”

Section: Related Workmentioning

confidence: 99%

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A New Model for the Multi-Objective Multiple Allocation Hub Network Design and Routing Problem

2019

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In this paper, we propose a new model for the multi-objective multiple allocation hub network design and routing problem which contains determining the location of hubs, the design of hub network, and the routing of commodities between source-destination pairs in the given network. The selected hubs are not assumed to be fully connected, and each node and arc in the network has capacity constraints. The multiple objectives of the problem are the minimization of total fixed and transportation costs and the minimization of the maximum travel time required for routing. We propose a mathematical formulation for the multiobjective problem and present a meta-heuristic solution based on a well-known multi-objective evolutionary algorithm. Using the proposed formulation, we are able to find the optimal solution for small networks of five nodes and seven nodes. To evaluate the performance of our heuristic approach on real data, the computational experiments are conducted on Turkish postal system data set. The results demonstrate that our heuristic approach can find feasible solutions to the problem in reasonable execution time, which is less than 10 min.INDEX TERMS Capacitated hub location problem, heuristic algorithms, mathematical model, pareto optimization, routing and network design.

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Multiple objective multiple allocation hub location problem

Cited by 5 publications

References 19 publications

Robust and fuzzy goal programming optimization approaches for a novel multi-objective hub location-allocation problem: A supply chain overview

Robust and fuzzy goal programming optimization approaches for a novel multi-objective hub location-allocation problem: A supply chain overview

Designing Airline Hub-and-Spoke Network and Fleet Size by a Biobjective Model Based on Passenger Preferences and Value of Time

A New Model for the Multi-Objective Multiple Allocation Hub Network Design and Routing Problem

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