Compromise of Two-criteria Final Payoff of the Game Ship Control in Collision Situations

Abstract

The essence of the article is the use of multi-criteria static optimization of object motion, based on a set of optimal Pareto points in the space of possible variants of solutions for a new approach to the problem as a game control. Using the example of the two-criteria optimization of the final payoff of the object game control during the safe evasion of the encountered objects, six methods of multi-criteria static optimization are presented—Bentham's utilitarian rule, Rawls's principle of justice, Salukvadze's benchmark, Benson's weighted sums, Haimes's constraints, and goal-oriented programming. In the end, the results obtained by the two-criteria optimization are compared with regard to the values of the components of the final game payoff—the risk of collision and the deviation of the object from the safe route of the set trajectory of movement. The directions for the development of multi-criteria optimization methods, both static and dynamic, and the game are indicated.

Keywords

• collision situation
• pareto optimal
• multi-criteria static optimization
• bentham's utilitarian rule
• rawls's principle of justice
• salukvadze's benchmark
• benson's weighted sums
• haimes's constraints