The Recent Advances in Combinatorial Optimization and Its Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".
Deadline for manuscript submissions: 15 June 2024 | Viewed by 1235
Special Issue Editor
Interests: optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, the combinatorial optimization problem (COP) has impacted various fields such as industry, transportation, telecommunication, national defense, bioinformatics, finance and life (see Special Issue "Combinatorial Optimization Problems in Planning and Decision Making"). Moreover, traditional operational research methods are primarily used to solve combinatorial optimization problems. However, with the increasing difficulty of practical applications and the increasing demands for real-time optimization, a limitation of the traditional operation optimization algorithm is becoming increasingly serious. Many new methods using deep reinforcement learning have recently emerged to solve combinatorial optimization problems, which have the advantages of fast solving speed and strong model generalization ability, and provide a new way of thinking for solving combinatorial optimization problems.
This Special Issue will focus on the recent theoretical studies and methods used to solve combinatorial optimization problems. Topics include, but are not limited to, the following:
- combinatorial optimization;
- multi-objective combinatorial optimization;
- optimization;
- optimization in multimedia systems;
- stochastic algorithms for combinatorial optimization;
- metaheuristics for combinatorial optimization.
Dr. Tibor Szkaliczki
Guest Editor
Manuscript Submission Information
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Keywords
- combinatorial optimization
- multi-objective combinatorial optimization
- optimization
- optimization in multimedia systems
- stochastic algorithms for combinatorial optimization
- metaheuristics for combinatorial optimization
- graph optimization problems
- matroid optimization problems
- set cover problem
- scheduling
- VLSI routing
- knapsack problem
- bin packing
- computational compexity of optimization problems
- approximation algorithms
