Linear Programming Essay

1153 Words3 Pages

This project involves optimization of materials procurement, transportation in construction projects. With the thought of operations research, designed a objective function and constrained conditions for a materials procurement and transportation optimization model. According to data, simulates the cost and the method provided can be used to analyze the rule of materials procurement and transportation cost and make a correct decision and to solve the problem of analyzing and forecasting procurement and transportation costs of the main materials in construction projects.

INTRODUCTION:
A Large proportion of the construction cost is materials, so it may obtain great economic benefit if the material cost could be reduced by optimizing. Therefore …show more content…

Finally, from the findings of the study, suggestions of how linear programming method could be widely applied in decision making in construction would be offered.

BRIEF REVIEW OF LITERATURE:
Linear Programming is a powerful quantitative tool used by operations managers and other managers to obtain optimal solutions to problems that involve restrictions, such as the available materials, budgets, and labor. These problems are referred to as constraint optimization problems. There are numerous examples of linear programming applications including:
• Establishing locations for emergency equipment and work force that will minimize response time
• Determining optimal schedules for planes, pilots, and ground personnel
• Identifying the best set of worker-job assignments
• Developing optimal production schedules
• Developing shipping layouts that will minimize shipping costs
• Identifying the optimal blends of products in a …show more content…

The two general types of objectives are maximization and minimization. A maximization objective might involve cost, time, distance travelled. The objective function is a mathematical expression that can be used to determine the total profit for a given solution. Decision variables represent choices available to the decision maker in terms of amounts of either inputs or outputs. For example, some problems require choosing a combination of inputs to minimize total costs, while others require selecting a combination of outputs to maximize profits or revenues. Constraints are limitations that restrict the alternatives available to decision makers. There are three types of constraints, mainly less than or equal to (<=), greater than or equal to (>=), and simply equal to (=). A <= constraint implies an upper limit on the amount of some resource available for use. A >= constraint specifies a minimum that must be achieved in the final solution. The = constraint is more restrictive in the sense that it specifies exactly what a decision variable should equal. A linear programming model can consist of more than one constraints. The constraints of a given problem explains the set of all feasible combinations of decision variables; this set is referred to as the Feasible solution. Linear programming algorithms are designed to search the feasible solution space for the combination

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