Goal programming is a form of linear programming that allows for consideration of multiple, potentially conflicting goals in decision-making processes.
A heuristic is a strategy or method employed to solve problems more quickly when classic methods are too slow or fail to find an exact solution. It utilizes intelligent trial and error tactics and is often contrasted with algorithmic solutions, which are clearly defined, step-by-step procedures that guarantee a correct outcome.
An industrial engineer studies industrial productivity and implements recommended changes to optimize integrated systems comprising workers, materials, and equipment. This involves applying mathematical, physical, and social sciences combined with engineering principles and methods to improve system efficiency and productivity.
Linear programming is a mathematical technique used for optimization, particularly suited for scenarios involving constraints. This method assists in achieving the best possible outcome, such as maximizing profits or minimizing costs, under specified limitations.
Linear Programming (LP) is a mathematical method for determining a way to achieve the best outcome in a given mathematical model for decisions with numerous alternatives. LP is often used in business, economics, and engineering to maximize profit or minimize costs in processes with varying levels of inputs.
An objective function in linear programming is a mathematical statement that defines the goal of a decision-making problem, often aiming to maximize contribution or minimize costs based on the relationship between production factors.
Operations Research (OR) is a discipline that deals with the application of advanced analytical methods to help make better decisions. It involves the development and use of mathematical models to improve understanding and manage large-scale systems.
The shadow price represents the change in the optimal value of the objective function for a linear programming problem per unit increase in the right-hand side of a constraint.
The Simplex Method, or Simplex Algorithm, is a method used for solving linear programming problems by iteratively testing feasible solutions until reaching the optimal solution. Designed for computational efficiency, it is particularly well-suited for computer applications.
