APPLICATION OF MULTI-OBJECTIVE OPTIMIZATION IN AN OLIGOPOLY MARKET

Abstract

Modeling competitive behavior in oligopolistic markets through multiobjective optimization is closely linked to decision-making processes in economic systems. This study proposes an approach for identifying Pareto-optimal solutions using empirical export data of coking coal from Mongolia, Russia, and Australia. The Pareto-efficient equilibrium was obtained by transforming the multi-objective problem into a global optimization problem using the weighted sum scalarization technique based on Theorem 2 and solving it in MATLAB. Two experimental models were constructed using different price–cost function structures. The numerical results indicate that the optimal export quantities of the three countries are highly dependent on the functional form of the price–cost relationship. When the price function exhibits quadratic growth, equilibrium supply levels shift toward higher values. These findings demonstrate the significant influence of price elasticity and cost structure on strategic decision-making in resource-based oligopoly markets. The results may provide useful insights for developing optimal export strategies in markets with oligopolistic characteristics.