Bottleneck Mitigation of Assembly Lines with Memetic Algorithms

Wen Ping Liu; Meng Wang; Zhen Jie Zhu

doi:10.4028/www.scientific.net/AMR.655-657.1631

Paper Titles

The Design of 12-Channels Acquisition and Storage System Based on FPGA and AD7492
p.1604

A Dual-Loop-Based Parallel Power Supply System
p.1609

Dual-Band BPF Using Simple SIR Structure
p.1614

Using FEA Simulation and Experimental Models of Flexible Substrates to Assist the Technology of Miniaturization of Electronic Devices
p.1619

Bottleneck Mitigation of Assembly Lines with Memetic Algorithms
p.1631

A Hybrid Population-Based Incremental Learning Algorithm for M-Machine Reentrant Permutation Flow-Shop Scheduling
p.1636

Cooperation Efficiency Analysis for Bargaining Based Assembly Scheduling
p.1642

Production Planning Optimization in F Company: A Scheduling Theory Case Study
p.1646

The Resource Conflicts Detecting Method of Virtual Manufacturing Cell Based on Bayesian Network
p.1650

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Bottleneck Mitigation of Assembly Lines with Memetic Algorithms

Abstract:

Bottlenecks heavily affect the material flow and workloads of assembly lines, and eventually constrain the productivity. The most economic way to eliminate or mitigate bottlenecks of a specific assembly line is to smooth the workloads at different stations towards a balanced system. This paper formulates a smoothness index, by which to measure the uniformity of workloads at serially located stations. To minimize the smoothness index, a Memetic algorithm is adopted and coding/decoding methods of the algorithm are devised. The effectiveness of the proposed algorithm is validated by a comparison with computing results of Package Lingo 11.0.