Research And Application Of Aggregate Production Planning Approach Under Uncertain Information Environment

A reasonable aggregate production planning has positive significance for responding to market demand, reducing waste in manufacturing process and the inventory of product. However, there are a large number of uncertain and imprecise factors in actual environment which caused great difficulties for making a production plan.This paper analyzes these uncertain factors in all aspects of production planning and decision-making process of current manufacturing enterprises and proposes a practical solution to develop aggregate production plan.Base on using fuzzy math to describe uncertain information, this paper establishes the fuzzy chance constrained programming model based on Credibility Theory arming at pursuing the maximum profit, and then the fuzzy model is translated into crisp equivalent. Considering factor of the maximum profit, the total overtime hours, a total amount of production shortages, staff turnover problem, this paper extends the aggregate production planning model and a multi-objective production planning model is established. A hybrid intelligent algorithm combined by fuzzy simulation, neural network and genetic algorithm is proposed to solve the multi-objective model. A human-computer interaction mechanism is introduced in order to continuously develop the production planning model. Considering it's hard to assess every object in our model for their different Magnitude from each other, a concept of relative value is introduced into the multi-solution decision-making process, which takes both objective consequence and subjective preference into account. The model and optimization Algorithm we proposed solved the problem that classic APP solutions detach far away from decision-maker's expectation. Finally, a numerical example is provided for illustrating the effectiveness of the solution we proposed.Upon all the above studies, an Aggregate Production Planning Management System under Uncertain Information Environment is designed, which applied theoretical results to practice.