A memetic algorithm-based heuristic for a scheduling problem in printed circuit board assembly

Authors:
Patcharaporn Neammanee;Manop Reodecha
Affiliations:
School of Applied Statistics, National Institute of Development Administration (NIDA), Serithai Road, Bangkaphi, Bangkok 10240, Thailand;Industrial Engineering Department, Engineering Faculty, Chulalongkorn University, Bangkok 10400, Thailand
Venue:
Computers and Industrial Engineering
Year:
2009

Citing 7
Cited 1

Models arising from a flexible manufacturing machine, Part I: minimization of the number of tool switches

Operations Research
A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation

Computers and Industrial Engineering
Multiple setup PCB assembly planning using genetic algorithms

Computers and Industrial Engineering
Group sequencing a PCB assembly system via an expected sequence dependent setup heuristic

Computers and Industrial Engineering
A branch-and-bound algorithm for the early/tardy machine scheduling problem with a common due-date and sequence-dependent setup time

Computers and Operations Research
Hybrid genetic algorithm for multi-time period production/distribution planning

Computers and Industrial Engineering - Special issue: Selected papers from the 30th international conference on computers; industrial engineering
Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups

Computers and Industrial Engineering - Special issue: Group technology/cellular manufacturing

A single machine carryover sequence-dependent group scheduling in PCB manufacturing

Computers and Operations Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

This research develops a memetic algorithm to solve Printed Circuit Board (PCB) scheduling with sequence-dependent setup times on a single machine with constrained feeder capacity. The objective of the scheduling problem is to minimize the total weighted tardiness. A memetic algorithm-based heuristics is developed by integrating a genetic algorithm, Minimum Slack Time (MST) scheduling rule, ''Keep Tool Needed Soonest'' (KTNS) policy, and a local search procedure. Application of the MA results in two outcome plans: a scheduling plan and a feeder setup plan. Numerical experiments show that compared to a number of commonly used dispatching rules, the memetic algorithm provides better solutions in term of minimum total weighted tardiness. Even the computation is the highest, it still practical. Calibration of MA parameter values is also explored in this study.