Mathematical models and empirical analysis of a simulated annealing approach for two variants of the static data segment allocation problem

Sen, Goutam; Krishnamoorthy, Mohan; Rangaraj, Narayan; Narayanan, Vishnu

doi:10.1002/net.21675

Cited by 12 publications

(6 citation statements)

References 41 publications

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“…Sen et al [17] solved DAP problem by applying simulated annealing (SA) algorithm [18] and evaluated their results using standard benchmarks in CPLEX. As evaluation result, they showed that SA algorithm works better in reasonable time.…”

Section: State-of-the-art In Methods For Solving Data Allocation Probmentioning

confidence: 99%

Data allocation in distributed database systems: a novel hybrid method based on differential evolution and variable neighborhood search

Lotfi¹

2019

SN Appl. Sci.

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Data allocation problem (DAP) in distributed database systems is a NP-hard optimization problem with significant importance in parallel processing environments. The solution of problem aims to minimize the total cost of transactions and settlement of queries in which he main cost regards to the data transmission through the distributed system. These costs are affected by the strategy how to allocate fragments to the sites. Researchers have been solving this challenging problem by applying soft computing methods especially evolutionary algorithms. This study proposes a novel hybrid method based on differential evolution (DE) algorithm and variable neighborhood search (VNS) mechanism for solving DAP problem. The suggested hybrid method (DEVNS) aims to increase the performance of DE algorithm by applying effective selection and crossover operators. Moreover, DEVNS goals to improve the solutions found so far using VNS technique. By applying VNS, more promising parts of search space can be extracted. Eventually, the introduced DEVNS explores the search space via DE and fulfills more exploitation by neighborhood search mechanism. Performance of proposed DEVNS is experimentally evaluated against nine state-of-the-art methods using well-known benchmarks reported in literature. Obtained results exhibits that proposed DEVNS takes the first position for 13 of 20 test problems. Likewise, Friedman aligned rank test is carried out to demonstrate that there is significant statistical difference between all methods.

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Section: State-of-the-art In Methods For Solving Data Allocation Probmentioning

confidence: 99%

Data allocation in distributed database systems: a novel hybrid method based on differential evolution and variable neighborhood search

Lotfi¹

2019

SN Appl. Sci.

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“…The HLP has been studied in several contexts including telecommunications, parcel delivery systems, airline hub design and transportation networks (Ç etiner et al [10], Ernst and Krishnamoorthy [14,15,16], Jaillet et al [20], Klincewicz [24], Powell and Sheffi [37], Sen et al [39,40]). There are a few surveys which review early and recent works on HLP classification, modelling, and solution methodologies (Alumur and Kara [3], Campbell et al [8], Farahani et al [17]).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…While a hub topology achieves decreased costs through flow aggregation, we are not assured that there will always be a path in the network for flow between each origin-destination pair in the network. In particular, in data location problems, content delivery networks employ hub networks to utilise multiple servers for responding to customer demands (Sen and Krishnamoorthy [38], Sen et al [40]). This context is especially important for Videoon-Demand systems, where content and videos are distributed among multiple servers and end-users are constantly connected to the server network (Sen et al [39]).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

The 2-allocation p-hub median problem and a modified Benders decomposition method for solving hub location problems

Mokhtar

Krishnamoorthy

Ernst

2019

Computers & Operations Research

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We study the uncapacitated 2-allocation p-hub median problem (U2ApHMP), which is a special case of the well-studied hub median problem. The hub median problem designs a hub network in which the location of p hubs needs to be decided (the hubs are fully interconnected). The other nodes (known as access nodes) in the hub median problem are then allocated to one or many hubs. In the U2ApHMP, each access node is allocated to exactly two hubs. We discuss how this problem provides an alternative network design option for well-known p-hub median problems. We show its relevance and usefulness in the context of survivable network design and show that it addresses network survivability, a feature that has often been largely overlooked in hub network design research to date. We show that U2ApHMP is NP-hard even for a fixed/known set of hubs. We propose a mathematical formulation and develop a modified Benders decomposition method for this problem. In this, we convert the corresponding subproblems to minimum cost network flow problems. This allows us to solve large instances efficiently. We believe that, while our resulting method solves the U2ApHMP efficiently, it is also generalisable and can potentially be employed for solving other classes and types of hub location problems too.

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“…Following seminal works of O'Kelly (1986,1987), a few hub median problems were introduced and formulated by Campbell (1994Campbell ( , 1996. HLPs have been studied in several contexts including telecommunications, parcel delivery systems, airline hub design and transportation networks (see Klincewicz (1998); Sen et al (2015Sen et al ( , 2016; Krishnamoorthy (1996, 1998a,b);Ç etiner et al (2010); Jaillet et al (1996); Powell and Sheffi (1983)). There have been many well-known complex network design problems which have been analysed and implemented using a hub location model/framework.…”

Section: Introductionmentioning

confidence: 99%

“…O'Kelly (1987) implemented USApHMP in order to analyse the 25-city airline passengers network, known as Civil Aeronautics Board (CAB) dataset. Tan and Kara (2007) analysed Turkey's Cargo Delivery network of 81 cities through the implementation of a hub location model. Gelareh et al (2010) used hub network design to address a liner shipping problem.…”

Section: Introductionmentioning

confidence: 99%

An intermodal hub location problem for container distribution in Indonesia

Mokhtar

Redi

Krishnamoorthy

et al. 2019

Computers & Operations Research

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In this paper, we extend traditional hub location models for an intermodal network design on a sparse network structure. While traditional hub location problems have been employed for developing network designs for many specific applications, their general assumptions -such as full connectivity, uniform transfer mode, and direct connections between access nodes and hubs -restrict their direct applicability to real-world logistics problems in several ways. In many network design contexts, the usage of versatile transfer modes and hubs is required due to different pricing of modes and topological considerations. In this paper, we extend the traditional hub location problem by incorporating three transfer modes and two kinds of hubs. As an important additional modification, we do not assume that the underlying network is fully connected, or that hubs and access nodes are directly connected. The context for our modelling is intermodal container movements in an archipelago. We develop and formulate an intermodal hub location problem. We show that this problem is NPhard. Furthermore, a dataset for intermodal hub location problem is provided, based on a real-world container distribution problem in Indonesia. This dataset involves three modes of transport and a sparse network structure. We perform computational experiments and analyse our computational results. Our model provides insights for decision making and determining pricing policies for the desired levels of network flow.

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Mathematical models and empirical analysis of a simulated annealing approach for two variants of the static data segment allocation problem

Cited by 12 publications

References 41 publications

Data allocation in distributed database systems: a novel hybrid method based on differential evolution and variable neighborhood search

Data allocation in distributed database systems: a novel hybrid method based on differential evolution and variable neighborhood search

The 2-allocation p-hub median problem and a modified Benders decomposition method for solving hub location problems

An intermodal hub location problem for container distribution in Indonesia

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