Abstract
Mixed-model straight/U-shaped assembly line has been recognized as a relevant component of Just-In-Time (JIT) production line system. For this system, “Heijunka” design is also challenged as both the task assignment and the production sequence affect the workload imbalance among workstations. In this context and recognizing uncertain task time environment that is often observed in actual manufacturing scene, this research addresses the Line Balancing Problem (LBP) and the Product Sequencing Problem (PSP) jointly and proposes a mathematical model with stochastic task time which is subjected to normal distribution. The objectives of this model are to maximize line efficiency and to minimize the variation of work overload time. A Multi-objective Genetic Algorithm (MOGA) and an Ameliorative Structure of Multi-objective Genetic Algorithm (ASMOGA) with Priority-based Chromosome (PBC) are applied to solve this problem. At last, this research conducts an experimental simulation on a set of benchmark problems to verify the outperformance of the proposed algorithm.
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