Research On Order Acceptance And Scheduling Strategy Of Making To Order Under Capacity Constraints

In order to quickly respond to customer needs,more and more enterprises are shifting their production model from making to stock to making to order.In the model of making to order,enterprises can respond to customers’ flexible demands and reduce unnecessary inventory.However,when a company receives orders from multiple customers within a certain production cycle,due to each customer having different expected order delivery dates and the latest acceptable order delivery dates,not being able to deliver orders within the customer’s expected dates can bring a delay cost to the enterprise.In order to achieve maximum revenue,enterprises need to review orders received,combine order information such as production capacity,order revenue,and customer expected delivery dates,determine which customers’ orders to accept,and schedule orders to fully utilize production capacity,minimize the delay in order delivery time,and minimize losses caused by delayed delivery orders.In order to avoid accepting too many orders,resulting in insufficient production capacity,or increasing delay penalty costs due to unreasonable production scheduling,it is necessary to consider both the factors of order acceptance and production scheduling.This article takes an enterprise with limited production capacity as a single machine production system with limited order processing capacity.At the beginning of a production cycle,the enterprise knows the information of all orders within that production cycle.Considering limited production capacity and delay penalty costs,in order to maximize profits,the enterprise should make order acceptance and production scheduling decisions,and construct a static mathematical model for order acceptance and production scheduling.We also considered the situation where orders arrive randomly after the start of the production cycle and the order information is unknown.When a new order arrives,the enterprise needs to make order acceptance and production scheduling decisions based on the current order processing status,production capacity,and newly received order information.Based on the time index formula,a dynamic mathematical model is constructed based on this problem.In the process of constructing the model,this article adds constraints that fully utilize production capacity on the basis of the existing capacity constraints,and establishes a new mathematical model for order acceptance and production scheduling problems.Therefore,this thesis designs a Tabu search algorithm to solve the problem.In the design of the algorithm,greedy rules are used to select orders with high returns and short production times as the initial solution,and then through the designed algorithm process,the optimal solution or approximate optimal solution is found quickly.In this thesis,several examples are generated according to the general case generation method for such problems.By comparing the results of Tabu search algorithm and Branch and bound algorithm,the effectiveness of the algorithm is verified;The Gantt chart of production schedule obtained according to the solution results also meets the constraints of making full use of capacity in the mathematical model,which verifies the effectiveness of the model.By solving the examples with orders of25 and 100,it was found that the production capacity of the enterprise directly affects the decision of the enterprise to accept orders and the profits obtained from the orders.Further solving examples of different delivery dates and latest delivery dates for orders,analyzing the results,it was found that customers’ longer delivery deadlines for orders can effectively reduce the number of delayed orders,reduce delay costs,and increase revenue for enterprises.