Simple and U-type Assembly Line Balancing by Using an Ant Colony Based Algorithm

Adil Baykasoğlu,Türkay Dereli

doi:10.3390/mca14010001

Abstract

In this paper, an Ant Colony Optimization (ACO) based heuristic algorithm is proposed for solving simple (straight line) and U-shaped assembly line balancing problems (ALBP). The paper makes one of the first attempts to show how ACO heuristic can be used to solve U-shaped ALBP. A new algorithm is proposed in this paper that seamlessly integrates COMSOAL algorithm, Ranked Positional Weight Heuristic (RPWH) and an ACO based heuristic in order to obtain good solutions to simple and U-shaped ALBPs. The result of the computational study has shown that the proposed algorithm is effective in solving simple/U-shaped line balancing problems.

Highlights

assembly line balancing problems (ALBP) relates to a finite set of work elements or tasks, each having an operation processing time and a set of precedence relations, which specify the permissible orderings of the tasks
In the original COMSOAL process task selection for station assignment is made randomly, in Ant Colony Optimization (ACO) process this is achieved by pheromone quantity update and ranked positional weight values as shown in step 5
This is the process of integrating ACO with COMSOAL [2] and Ranked Positional Weight [22] heuristics

Summary

INTRODUCTION

ALBP relates to a finite set of work elements or tasks, each having an operation processing time and a set of precedence relations, which specify the permissible orderings of the tasks. The fundamental line-balancing problem is how to assign a set of tasks to an ordered set of workstations, such that the precedence relations are satisfied and some measure of performance is optimized [17]. The first group determines the tasks assigned to a set of workstations with the same cycle time; each task has a deterministic duration and must be performed in only one of the workstations. It is observed that genetic algorithms are more frequently used in modeling and solving simple and U-shaped ALBPs than the other meta-heuristics. The number of studies on U-shaped ALBPs is limited in comparison to simple ALBPs. In this research paper, an ACO based algorithm is proposed for solving simple and U-shaped ALBPs with the aim of maximizing the line performance (or minimizing the number of workstations). The proposed algorithm found promising solutions for each problem in short computational times

ANT COLONY BASED ALGORITHM FOR SIMPLE AND U-TYPE ALBP

COMPUTATIONAL STUDY

CONCLUSIONS