الفهرس 
Solving u-shaped assembly line balancing problem under uncertainty
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Abstract
The U-shaped assembly line balancing problem is one of the industrial problems that are related to optimizing the assignment of the tasks in order to balance the assembly work in a U-line. This thesis concerns with solving such problem under uncertainty. The contribution of the thesis consists of four studies. The first study concerns with solving the chance-constrained U-shaped assembly line balancing problem. The developed approach for solving it is greedy randomized adaptive search procedure. The second study concerns with solving stochastic multi-manned assembly line balancing problem. The developed approach for solving it is an artificial immune system algorithm. The third study combines both of U-shaped and multi-manned concepts of the previous two study forming new problem called chance-constrained multi-manned U-shaped assembly line balancing problem. In the third study, additional constraints are added to the mathematical model related to the area of the tasks. The problem is solved using stochastic local search algorithm. The fourth study is a comprehensive study that solves all the problems of the previous studies using an adaptive differential evolution algorithm. The computational results of all studies consist of 71 adapted problems selected from well-known benchmarks.