Multi-Objective linear programming and its Mathematical
DOI:
https://doi.org/10.29070/bc320d38Keywords:
Multi-objective optimization, Pareto efficiency, linear programming, goal programming, decision theory, optimization modelsAbstract
Multi-Objective Linear Programming (MOLP) has emerged as a crucial analytical framework for solving optimization problems involving multiple, often conflicting objectives. Unlike classical linear programming, which focuses on a single objective, MOLP provides a structured approach to balancing trade-offs among competing goals. This article examines the theoretical foundations, mathematical formulation, solution methodologies, and diverse applications of MOLP. Special emphasis is placed on Pareto optimality, scalarization techniques, and recent computational developments. The study further explores interdisciplinary applications across economics, engineering, environmental science, and public policy, highlighting the growing significance of MOLP in modern decision-making environments.
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