Emerging Topics in Multi-objective Optimization and Its Applications

Dear Colleagues,

Multi-Objective Optimization Problems (MOPs) are common in many application domains, such as engineering, management, operation research, finance, medical science, computer science, and informatics. Such problems commonly involve conflicting objectives, a huge number of variables, nonlinear relationships, a variety of soft and hard constraints, and a dynamic and uncertain environment, and as such pose great challenges.

Solving a MOP without a priori articulation of the objective preferences commonly results in more than one solution. Over more than two decades, Pareto-based optimization, which is based on a vector-based domination relation among the candidate solutions, has become a leading approach to solving MOPs. It aims to find the set of optimal solutions and their associated performance vectors, i.e., the Pareto-optimal set and front. The main advantage of this approach is that it exposes the performance tradeoffs of the optimal solution, which supports decision making on the selected solution. It should be noted that, although the research in the field of multi-objective optimization has progressed significantly in the last two decades, the complexity of real-world problems has substantially increased as well.

The scope of this Special Issue includes, but is not limited to, the following topics:

• Multi/many objective evolutionary and other population-based algorithms;
• Interactive multi-objective optimization;
• Benchmarking and performance indicators;
• Multi-objective machine learning;
• Surrogate-based methods in multi-objective optimization;
• Theoretical aspects of multi-objective optimization;
• Applications and case studies;
• Multi-objective optimization in a dynamic and uncertain environment;
• Preference handling techniques;
• Constraint handling techniques;
• Visualization techniques;
• Surrogate-assisted techniques;
• Theoretical analysis of convergence and scalability.

Dr. Oren E. Nahum
Dr. Adham Salih
Dr. Amiram Moshaiov
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 submissions that pass pre-check are 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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.

• optimization
• multi-objective optimization
• non-dominated solutions
• Pareto front
• exact algorithms
• mathematical programming
• heuristics
• metaheuristics
• evolutionary algorithms
• population-based algorithms