Pareto Optimality in a Static Competitive Decision-Making Model
Abstract
Purpose: Some applied problems, such as forecasting, selecting, assignment, allocation, diagnostics or multi-agent management, often require providing optimal interaction between agents. The purpose of this research is constructing an algorithm and simple software for solving a game-theoretic model of multi-agent interaction of competitive type, using Pareto optimum and compromise solution, which would process data from a large number of participants in each project. Results: An algorithm is built for solving a static competitive decision-making model, which searches for Pareto-optimal solutions in non-cooperative games and for a compromise project. This model is formalized as a family of different non-cooperative games. Each game is defined for some project and requires a adoption of a positive or negative decision by every player. The players' incomes are defined as values of payoff functions on the set of n-tuples from their decisions for the relevant projects. We have to solve each non-cooperative game and then, from a set of solutions, to choose a compromise one with the help of an algorithm of finding a compromise solution in order to emphasize the priority project (one or more). The existence of static competitive decision-making model solution is proved and a numerical example is given. Practical relevance: The proposed algorithm can be recommended as a tool to clarify or confirm the optimal solution about the alleged participation in a certain project.Published
2015-10-20
How to Cite
Grigorieva, X. (2015). Pareto Optimality in a Static Competitive Decision-Making Model. Information and Control Systems, (5), 124-129. https://doi.org/10.15217/issn1684-8853.2015.5.124
Issue
Section
Control in social and economic systems