Forthcoming articles

International Journal of Metaheuristics

International Journal of Metaheuristics (IJMHeur)

These articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Register for our alerting service, which notifies you by email when new issues are published online.

Open AccessArticles marked with this Open Access icon are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.
We also offer which provide timely updates of tables of contents, newly published articles and calls for papers.

International Journal of Metaheuristics (2 papers in press)

Regular Issues

  • A Tabu Search Approach for a Virtual Networks Splitting Strategy Across Multiple Cloud Providers   Order a copy of this article
    by Marieme Diallo, Alejandro Quintero, Samuel Pierre 
    Abstract: This paper addresses the problem of computational and networking resources embedding across multiple independent cloud providers (CPs). We focus on the splitting phase problem by proposing a virtual network requests (VNRs) splitting strategy, which aims at improving the performance and the quality of service (QoS) of resulting mapped VNR segments. We formalize our splitting strategy as a mathematical maximization problem with constraints by using an Integer Linear Program (ILP). Since the VNRs splitting process is classified as an NP-hard problem, we propose a metaheuristic approach based on the Tabu Search (TS), in order to find good feasible solutions in polynomial solving time. The simulations results obtained show the efficiency of the proposed algorithm, in comparison with the exact method and an other baseline approach. Solution costs are on average close to the upper bounds, with an average gap ranging from 0% to a maximum of 2.97%, performed in a highly reduced computing time.
    Keywords: Cloud computing; virtualized network infrastructures; resource splitting; optimization; metaheuristics; Tabu Search.

  • Solving high dimensional multimodal continuous optimization problems using hybridization between particle swarm optimization variants   Order a copy of this article
    by Hugo Deschenes, Caroline Gagne 
    Abstract: This paper presents a comparison between three new hybridizations using three Particle Swarm Optimization (PSO) variants: The Barebones PSO (BPSO), the Comprehensive Learning PSO (CLPSO) and the Cooperative Learning PSO (CoLPSO). The goal of these hybridizations is to improve the exploration and the exploitation of the search space from these three variants and contributes to PSO on high scale continuous optimization problems. The performance of these three new hybrids, named HCLBPSO-Half, HBPSO+CL and HCoCLPSO, are compared with the original methods on which they are based. The comparison is done using 6 classical continuous optimization functions with dimensions set to 50, 100 and 200, and all 15 continuous optimization functions from the CEC15 benchmark with dimensions set to 10, 30, 50 and 100. The results are compared using the mean and median of executions.
    Keywords: metaheuristics; continuous optimization; particle swarm optimization; hybridization; variants; high dimensional problems.