Assembly flexible job-shop scheduling problem with preemption and batch delivery system considering environmental impacts

Assembly flexible job-shop scheduling problem with preemption and batch delivery system considering environmental impacts


Assembly flexible job-shop scheduling problem with preemption and batch delivery system considering environmental impacts

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: Assembly flexible job-shop scheduling problem with preemption and batch delivery system considering environmental impacts

ارائه دهنده: Provider: Maryam Hajibabaie

اساتید راهنما: Supervisors: Dr. Javad Behnamian

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr. Amirsaman Kheirkhah - Dr. Nafiseh Soleimani

زمان و تاریخ ارائه: Time and date of presentation: October 2020

مکان ارائه: Place of presentation:

چکیده: Abstract: This study investigates the flexible Job-shop scheduling problem by considering criteria cleaner production, interruption of jobs and batch delivery system. In this problem, the release date for entering jobs in the system is considered and parts are produced in the first stage in flexible Job-shop environment and then in the second stage are assembled in flow shop environment to produce the final products. After assembly, the products are sent to customers in batches. The aims are to minimize the cost of the maximum completion time, the cost of earliness and tardiness, the fuzzy cost of transportation, to minimize the fuzzy emission of carbon dioxide from vehicles, and to minimize the overall speed increase. In order to make the conditions under study more realistic, the cost of transportation and the emission of carbon dioxide are considered as triangular fuzzy numbers. For this purpose, first a mixed integer programming model was developed and since it is a multi-objective model, using the epsilon- constraint method, the multi-objective problem is converted to a single-objective problem and the problem was solved with Lagrange relaxation algorithm. To evaluate the performance of the proposed relaxation algorithm, the results were compared with the Gams solution method. The results showed that the presented Lagrange relaxation algorithm is efficient. Given that the flexible job-shop scheduling problem is one of the most complexity problems of combinatorial optimization and the addition of other assumptions adds to the complexity of the problem, exact methods are not able to solve the problem on a large scale. Therefore, to solve the problem, an algorithm consisting of memetic and NSGAII algorithms is presented and Taguchi method is used to parameter setting. Also, in order to evaluate the performance of the proposed algorithm, according to some criteria for evaluating the performance of multiple algorithms, the results are compared with the results of the NSGAII algorithm. Keywords: Flexible job-shop scheduling problem with assembly, cleaner production, multi-objective optimization problem, Lagrange relaxation algorithm, algorithm consisting of memetic and NSGAII algorithms, triangular fuzzy number.

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