Abstract
In light of the imprecise and fuzzy nature of real production environments, the order acceptance and scheduling (OAS) problem is associated with fuzzy processing times, fuzzy sequence dependent set up time and fuzzy due dates. In this study, a genetic algorithm (GA) which uses fuzzy ranking methods is proposed to solve the fuzzy OAS problem. The proposed algorithm is illustrated and analyzed using examples with different order sizes. As illustrative numerical examples, fuzzy OAS problems with 10, 15, 20, 25, 30 and 100 orders are considered. The feasibility and effectiveness of the proposed method are demonstrated. Due to the NP-hard nature of the problem, the developed GA has great importance to obtain a solution even for big scale fuzzy OAS problem. Also, the proposed GA can be utilized easily by all practitioners via the developed user interface.
Highlights
Make to Order (MTO) is a production strategy in which manufacturing starts once a customer’s order is received
The order acceptance and scheduling (OAS) problem arises from the limited the production capacity that is characteristic of MTO environment
The aim of the present study is to develop a solution methodology based on a genetic algorithm (GA) approach in order to solve the fuzzy OAS problem in any scale
Summary
Make to Order (MTO) is a production strategy in which manufacturing starts once a customer’s order is received. In a MTO production environment, manufacturers offer more customized products to appeal their potential customers. While deciding which orders to accept, manufacturers have to simultaneously determine the schedule of these orders over a time frame that will make efficient use of their capacities. This problem, which involves the joint decision of order acceptance and order scheduling, is called the order acceptance and scheduling (OAS) problem [1]. The OAS problem arises from the limited the production capacity that is characteristic of MTO environment
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
