Optimizing Cost Stickiness Reduction Strategies with Genetic Algorithms

Cost stickiness, the phenomenon where costs do not decrease proportionately with decreases in revenue, presents a significant challenge in financial accounting practices, impacting the efficiency and profitability of organizations. In this study, we propose the application of genetic algorithms to explore and optimize strategies aimed at reducing cost stickiness within the Istanbul-stock market.The study begins by defining the problem of cost stickiness and its implications for financial accounting within the Istanbul-Bursa market context. Through a systematic approach, potential cost reduction strategies specific to the market dynamics are encoded as individuals within a genetic algorithm population. These strategies are evaluated using a fitness function designed to measure the degree of cost stickiness reduction achieved.Genetic operators, including selection, crossover, and mutation, are employed to iteratively evolve the population of strategies over successive generations, taking into account the unique characteristics of the Istanbul-Bursa market. Through this process, the algorithm converges towards optimal or near-optimal solutions for reducing cost stickiness in the local financial ecosystem.To validate the effectiveness of the optimized strategies within the Istanbul-Bursa market, historical data or simulation models specific to the market are utilized for performance evaluation. The study concludes with recommendations for the implementation of the optimized strategies within financial accounting practices in the Istanbul-Bursa market, emphasizing the importance of monitoring and adaptation to ensure sustained improvements in cost management and financial performance amidst the market dynamics.Overall, this research contributes to the advancement of cost management practices within the Istanbul-Bursa market by leveraging genetic algorithms to systematically optimize cost stickiness reduction strategies, thereby enhancing the efficiency and profitability of organizations operating in this dynamic economic environment.

کلیدواژه ها:

Cost stickiness ، Genetic algorithms ، Financial accounting ، Optimization ، Istanbul-Bursa market ، Cost reduction strategies