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In quantitative methods, optimization problems like the one presented—minimizing an objective function subject to constraints—form the backbone of decision-making in operations research, management science, and applied mathematics. The problem consists of two key components: the objective function, which represents the criterion to be optimized, and the constraint(s), which define the feasible region in which the solution must lie. In this context, the objective function is usually expressed as a linear or nonlinear mathematical equation, depending on the nature of the variables and relationships involved. Minimization problems aim to find the set of decision variable values that produce the lowest possible value of the objective function while satisfying _________ ____ ___ ___ ________ ______ ________ _____ __________.
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