HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY

Bibliographic Details
Main Author:	Norman, Susan K.
Language:	English
Published:	University of Cincinnati / OhioLINK 2001
Subjects:	PRINTED CIRCUIT BOARD ASSEMBLY HEURISTICS GENETIC ALGORITHMS CLUSTERING SET UP TIME
Online Access:	http://rave.ohiolink.edu/etdc/view?acc_num=ucin997881019

id	ndltd-OhioLink-oai-etd.ohiolink.edu-ucin997881019
record_format	oai_dc
spelling	ndltd-OhioLink-oai-etd.ohiolink.edu-ucin9978810192021-08-03T06:16:29Z HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY Norman, Susan K. PRINTED CIRCUIT BOARD ASSEMBLY HEURISTICS GENETIC ALGORITHMS CLUSTERING SET UP TIME The goal of the printed circuit board job-batching (PCB-JB) problem is to minimize the total manufacturing time (setup time and processing time) required to process a set of printed circuit board jobs on an insertion machine. PCBs are processed on a single-head, concurrent, pick-and-place machine that places components onto a board. The PCB-JB problem is a combinatorial optimization problem that is NP-hard thereby, in general, restricting optimal solution techniques to small instances. We have developed four heuristic approaches to solve the PCB-JB problem: a cluster analysis approach (clustering), a best-fit-decreasing bin-packing approach (BFDJB), a sequencing genetic algorithm approach (GASPP), and a grouping genetic algorithm approach (GGA). We randomly generated 80 problems and performed an experimental design to characterize the performance of these heuristics. Results show that there is not a best heuristic for all circumstances. Clustering obtains the best average solution quality and fastest execution time. For a small number of jobs in the set to be partitioned, the grouping genetic algorithm finds the best solutions often finding the optimal solution. For problems with a large number of jobs, clustering is preferred for problems with a small job size variance and the BFDJB heuristic is preferred for problems with a large job size variance. The execution time for the BFDJB heuristic is close to the clustering algorithm. The two genetic algorithms are slower. GGA requires over 30 hours for a problem that takes less than 18 seconds for the clustering heuristic. 2001-10-11 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin997881019 http://rave.ohiolink.edu/etdc/view?acc_num=ucin997881019 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection	NDLTD
language	English
sources	NDLTD
topic	PRINTED CIRCUIT BOARD ASSEMBLY HEURISTICS GENETIC ALGORITHMS CLUSTERING SET UP TIME
spellingShingle	PRINTED CIRCUIT BOARD ASSEMBLY HEURISTICS GENETIC ALGORITHMS CLUSTERING SET UP TIME Norman, Susan K. HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY
author	Norman, Susan K.
author_facet	Norman, Susan K.
author_sort	Norman, Susan K.
title	HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY
title_short	HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY
title_full	HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY
title_fullStr	HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY
title_full_unstemmed	HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY
title_sort	heuristic approaches to batching jobs in printed circuit board assembly
publisher	University of Cincinnati / OhioLINK
publishDate	2001
url	http://rave.ohiolink.edu/etdc/view?acc_num=ucin997881019
work_keys_str_mv	AT normansusank heuristicapproachestobatchingjobsinprintedcircuitboardassembly
_version_	1719433842120458240

HEURISTIC APPROACHES TO BATCHING JOBS IN PRINTED CIRCUIT BOARD ASSEMBLY

Similar Items