Uniformly Deployed Sets in Discrete Optimization: Theory and Applications

This paper aims at a specific class of discrete optimization problems, which found their applications in many areas, not excluding the design of service systems. Whenever an integer programming toolkit is used to solve a real-world instance, then the associated exact solving approaches embedded into common decision support tools may fail due to enormous amount of required computational resources. To avoid the aforementioned inconveniences, many sophisticated heuristic and metaheuristic algorithms have been developed to provide the decision-makers with a good solution in acceptable time. Currently, many genetic and evolutionary algorithms based on processing a population of solutions are gaining popularity. This paper summarizes prior studies, and gives short overview of available approaches to maintain the diversity and other useful features of the set of solution deployed uniformly. The theory of uniformly deployed set creation is accompanied by possible applications of the set in the field of large public service system designing.