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- Type of Document: Ph.D. Dissertation
- Language: Farsi
- Document No: 42650 (01)
- University: Sharif University of Technology
- Department: Industrial Engineering
- Advisor(s): Kianfar, Farhad
- Abstract:
- In recent years in assembly line balancing area many researchers have focused on identifying and modeling real world situations in assembly lines in order to obtain more suitable model. As a result many generalized models have been developed in assembly line balancing area. However, designing efficient algorithms to solve these generalized problems has just begun. In this study it is aimed to design efficient algorithms to solve one of these generalized problems. Specificcally two hybrid genetic algorithms (GA) are proposed to solve assembly line balancing problem with sequence dependent setup times. Scheduling of tasks in the stations has been less considered in the literature of assembly line balancing. Usually this decision is made by the operator as an operational decision. But in many cases in real world assembly line systems there are sequence dependent setup times between tasks and therefore the optimal or near optimal sequence of tasks must be determined. In this study two GAs are proposed to solve the assembly line balancing problem with sequence dependent setup times.The problem considered in this study involves two kind of decision making: determining the sequence of tasks and assigning them to stations. In the proposed Gas a tabu search and a dynamic programming algorithm is used to assign tasks to stations, considering the sequence of tasks. Also new mutation operators are proposed and the operators and parameters of the GAa are selected using the design of experiments method
- Keywords:
- Assembly Line ; Sequence Dependent Setup ; Genetic Algorithm ; Dynamic Programming ; Experimental Design
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