Abstract
This paper investigates Aggregate Production Planning (APP) model in a multi-plant producing multi-product to satisfy portion of fully deterministic demand in several cities for short term planning horizon. A Preemptive Goal Programming (PGP) approach is proposed with different scenarios to solve the APP model with conflicting multi-objective functions in order to maximize the total net profit with limited investment (budget), limited storage space, production capacity, and resources of the company. The proposed PGP model is also used to minimize the total production, inventory, transportation and defective items costs with optimum transportation pattern. A model is optimality solved and validated for a small numeric example of production planning problem with the results of optimal solutions for different scenarios obtained using optimization software LINGO package. Keywords: Aggregate production planning, Linear programming, Multi-objective criteria, Preemptive Goal Programming, Transportation .
Highlights
Aggregate Production Planning (APP) is a process which assist the manufacturer to balance capacity and demand in such away that costs are minimized over a short term planning horizon from approximately 3 to 18 months into the future
Mathematical linear programming optimization technique is successfully utilized in solving management problems of single objective function subjected to linear constraints, but it has a major limitation where it is inadequate technique for problems of more than single objective function, Goal Programming (GP) is a suitable technique to solve models with multiple objective functions
Each objective function is considered as a goal and the technique seeks to minimize the deviations between the desired goals and the actual results to be obtained according to the assigned priorities [5]
Summary
APP is a process which assist the manufacturer to balance capacity and demand in such away that costs are minimized over a short term planning horizon from approximately 3 to 18 months into the future. The fuzzy goal programming approach was applied to minimize total production, inventory, and rate of change in workforce costs. The designed model attempts to minimize total costs of change in labor levels, matching capacity with limited warehouse spaces and available budget. Stephen and Leung, Yue Wu [13] use goal programming to solve APP problem with multi-objectives using LINGO software package. This paper develops APP model consists of multiple conflicting objective functions with different scenarios, used to solve multi-plant, multi-product production problem, where all finished products should be shipped to several cities to satisfying some. Preemptive Goal Programming (PGP) technique is used to solve the model to minimize the total production, transportation, stock inventory and defective items costs, within a limited budget (investment) as the first priority, and to maximize the net profit over the planning horizon as the second priority.
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