Special Issue "Optimization Algorithms for Allocation Problems"

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".

Deadline for manuscript submissions: 31 August 2020.

Special Issue Editors

Dr. Eduardo Lalla-Ruiz
Guest Editor
Faculty of Behavioural, Management and Social Sciences, University of Twente, 7500 AE Enschede, The Netherlands
Interests: operations research; artificial intelligence; mathematical programming; logistics
Special Issues and Collections in MDPI journals
Dr. Jesica de Armas
Guest Editor
Department of Economics and Business, Universitat Pompeu Fabra, Ramon Trias Fargas, 25-27 08005 Barcelona, Spain
Interests: combinatorial optimization; metaheuristics; simulation; machine learning; logistics
Dr. Eduardo Segredo
Guest Editor
Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna, 38200 San Cristóbal de La Laguna, Spain
Interests: evolutionary computation; meta-heuristics; hyper-heuristics; single/multi/many-objective optimization; machine learning

Special Issue Information

Dear Colleagues,

Allocation problems are a fundamental type of optimization problem in many application areas (e.g., logistics, manufacturing, telecommunications, healthcare). Their main goal is to determine the allocation of resources such as items, workforce, assets, etc. to tasks, activities or spaces, among many others, while optimizing one or several given objective functions.

In optimization, there are several ways to find solutions for allocation problems. They can be broadly divided into exact, approximate, and hybrid techniques. At the same time, depending on the size of the solution space, as well as on the structure of the allocation problem, one can select one or another type of technique to be developed or applied. In this context, recent advancements in optimization methods, as well as novel application cases, have fostered the development of algorithms with the goal of providing high-quality solutions in short periods of time. Further, advancements in the development of efficient exact approaches have permitted an understanding of the problem and the performance evaluation of approximate approaches.

Considering the previous discussion, this Special Issue is aimed at bringing and presenting original research and state-of-the-art developments in algorithmic approaches for solving allocation problems. We also welcome innovative research and real-world cases addressing new problem variants. 

Dr. Eduardo Lalla-Ruiz
Dr. Jesica de Armas
Dr. Eduardo Segredo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Allocation problems
  • Optimization algorithms
  • Mathematical programming
  • Approximate approaches (e.g., heuristics, metaheuristics)
  • Discrete and continuous optimization
  • Experimental evaluation of algorithms in allocation problems

Published Papers (1 paper)

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Open AccessArticle
A Novel Hybrid Metaheuristic Algorithm for Optimization of Construction Management Site Layout Planning
Algorithms 2020, 13(5), 117; https://doi.org/10.3390/a13050117 - 06 May 2020
Symbiotic organisms search (SOS) is a promising metaheuristic algorithm that has been studied recently by numerous researchers due to its capability to solve various hard and complex optimization problems. SOS is a powerful optimization technique that mimics the simulation of the typical symbiotic [...] Read more.
Symbiotic organisms search (SOS) is a promising metaheuristic algorithm that has been studied recently by numerous researchers due to its capability to solve various hard and complex optimization problems. SOS is a powerful optimization technique that mimics the simulation of the typical symbiotic interactions among organisms in an ecosystem. This study presents a new SOS-based hybrid algorithm for solving the challenging construction site layout planning (CSLP) discrete problems. A new algorithm called the hybrid symbiotic organisms search with local operators (HSOS-LO) represents a combination of the canonical SOS and several local search mechanisms aimed at increasing the searching capability in discrete-based solution space. In this study, three CSLP problems that consist of single and multi-floor facility layout problems are tested, and the obtained results were compared with other widely used metaheuristic algorithms. The results indicate the robust performance of the HSOS-LO algorithm in handling discrete-based CSLP problems. Full article
(This article belongs to the Special Issue Optimization Algorithms for Allocation Problems)
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