Abstract

Mixed-model U-shaped assembly line balancing problems (MMUALBP) is known to be NP-hard resulting in it being nearly impossible to obtain an optimal solution for practical problems with deterministic algorithms. This paper pre-sents a new evolutionary method called combinatorial optimisation with coincidence algorithm (COIN) being applied to Type I problems of MMUALBP in a just-in-time production system. Three objectives are simultaneously considered; minimum number workstations, minimum work relatedness, and minimum workload smoothness. The variances of COIN are also proposed, i.e. CNSGA II, and COIN-MA. COIN and its variances are tested against a well-known algo-rithm namely non-dominated sorting genetic algorithm II (NSGA II) and MNSGA II (a memetic version of NSGA II). Experimental results showed that COIN outperformed NSGA II. In addition, although COIN-MA uses a marginal CPU time than CNSGA II, its other performances are dominated.

Highlights

  • An assembly line comprises a sequence of workstations through which a predefined set of tasks are performed repeatedly on product units while they are moving along the line

  • This paper presents a new evolutionary method called combinatorial optimisation with coincidence algorithm (COIN) being applied to Type I problems of Mixed-model U-shaped assembly line balancing problems (MMUALBP) in a just-in-time production system

  • This paper presents a novel evolutionary algorithm

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Summary

Introduction

An assembly line comprises a sequence of workstations through which a predefined set of tasks are performed repeatedly on product units while they are moving along the line. It was originally developed to support mass production of single homogeneous standardised commodity to gain a competitive unit cost. General-propose machines with automated tool changing equipment and highly flexible operators are necessary to realise an arbitrarily intermixed sequence of various models of a standardised product with similar process requirements to be assembled on the same line at negligible setup costs. The straight line cannot fully support the adoption of JIT principles to manufacturing especially in the utilisation of multi-skilled operators. Such companies as Allen-Bradley and GE have replaced their traditional straight lines with U-shaped production lines, called U-lines hereafter [3]. A rather narrow U-shape is normally formed since both ends of the line are located closely

A C Front of the line
Multi-Objective Evolutionary Algorithms
MULB Problem
Objective Functions
Proposed Algorithm
Numerical Example
Comparison Heuristics
Comparison Metrics
Parameter Settings
Experimental Results
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