الفهرس | Only 14 pages are availabe for public view |
Abstract Mixed model two-sided assembly line are common indu Dial practice in the assembly of large-sized product such as buses and trucks. In a Mixed model two-sided as embly line, differenr assembly task are carried out on the same product in parallel at both left and right sides of the line. The decision problem of optimally balancing the assembly work among the stations with respect to some objective i known as the a sembly line balancing problem (ALBP). In this research a Genetic AlgoritJun is developed to solve the Single-model and Mixed-model Two-sided Assembly Line Balancing Problem with the objective of finding the minimum number of stations as well as the minimum number of mated-stations for a given cycle time. The developed heuristic algorithm specifies a new method for generating the initial population. It applies a hybrid crossover and a modified scramble mutation operators. Moreover, due to the nature of the two-sided assembly line balancing problem, a proposed station oriented procedure is adopted for assigning tasks to station. This procedure specifie the ide of the ta ks that have no preferred direction based on specific rules rather than a signing these tasks randomly. A computational study is presented to test the performance of heuristic algorithm and the side assignment rules. The results showed that the proposed side assignment rules are effective especially in large problems. The proposed method of generating the initial population is able to generate feasible solution allowing more diversity in the population. The by brid crossover and the modified scramble mutation are able to preserve the feasibility of all solutions throughout all the developed generations. The Genetic Algorithm is able to find the optimum or near optimum solutions within a limited number of iterations. |