Sarit Maitra

This study presents a population-based evolutionary optimization algorithm (Adaptive Differential Evolution with Diversification Strategies or ADEDS). The algorithm was initially developed using the sinusoidal objective function and subsequently evaluated with a wide-ranging set of 22 benchmark functions, including Rosenbrock, Rastrigin, Ackley, and DeVilliersGlasser02, among others. This work employs single-objective optimization in a two-dimensional space and runs ADEDS on each of these benchmark functions with multiple iterations. The optimization algorithms used in supply chain analytics have a direct impact on the efficiency and cost-effectiveness of supply chain operations. The findings reveal the effectiveness of ADEDS in finding better solutions, which implies its importance for improving supply chain efficiency, reducing costs, and enhancing overall performance.