Comparison of Different Approaches to the Cutting Plan Scheduling

Allocation of specific cutting plans and their scheduling to individual cutting machines presents a combinatorial optimization problem. In this respect, various approaches and methods are used to arrive to a viable solution. The paper reports three approaches represented by three discreet optimizati...

Full description

Bibliographic Details
Main Author: Peter Bober
Format: Article
Language:English
Published: Technical University of Kosice 2011-10-01
Series:Kvalita Inovácia Prosperita
Subjects:
Online Access:http://www.qip-journal.eu/index.php/QIP/article/view/35/23
id doaj-c25e7213987c44828758741ad41ad1e5
record_format Article
spelling doaj-c25e7213987c44828758741ad41ad1e52020-11-24T20:58:31ZengTechnical University of Kosice Kvalita Inovácia Prosperita1335-17452011-10-011514756Comparison of Different Approaches to the Cutting Plan SchedulingPeter BoberAllocation of specific cutting plans and their scheduling to individual cutting machines presents a combinatorial optimization problem. In this respect, various approaches and methods are used to arrive to a viable solution. The paper reports three approaches represented by three discreet optimization methods. The first one is back-tracing algorithm and serves as a reference to verify functionality of the other two ones. The second method is optimization using genetic algorithms, and the third one presents heuristic approach to optimization based on anticipated properties of an optimal solution. Research results indicate that genetic algorithms are demanding to calculate though not dependant on the selected objective function. Heuristic algorithm is fast but dependant upon anticipated properties of the optimal solution. Hence, at change of the objective function it has to be changed. When the scheduling by genetic algorithms is solvable in a sufficiently short period of time, it is more appropriate from the practical point than the heuristic algorithm. The back-tracing algorithm usually does not provide a result in a feasible period of time.http://www.qip-journal.eu/index.php/QIP/article/view/35/23optimizationschedulingback-tracinggenetic algorithmsheuristic algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Peter Bober
spellingShingle Peter Bober
Comparison of Different Approaches to the Cutting Plan Scheduling
Kvalita Inovácia Prosperita
optimization
scheduling
back-tracing
genetic algorithms
heuristic algorithm
author_facet Peter Bober
author_sort Peter Bober
title Comparison of Different Approaches to the Cutting Plan Scheduling
title_short Comparison of Different Approaches to the Cutting Plan Scheduling
title_full Comparison of Different Approaches to the Cutting Plan Scheduling
title_fullStr Comparison of Different Approaches to the Cutting Plan Scheduling
title_full_unstemmed Comparison of Different Approaches to the Cutting Plan Scheduling
title_sort comparison of different approaches to the cutting plan scheduling
publisher Technical University of Kosice
series Kvalita Inovácia Prosperita
issn 1335-1745
publishDate 2011-10-01
description Allocation of specific cutting plans and their scheduling to individual cutting machines presents a combinatorial optimization problem. In this respect, various approaches and methods are used to arrive to a viable solution. The paper reports three approaches represented by three discreet optimization methods. The first one is back-tracing algorithm and serves as a reference to verify functionality of the other two ones. The second method is optimization using genetic algorithms, and the third one presents heuristic approach to optimization based on anticipated properties of an optimal solution. Research results indicate that genetic algorithms are demanding to calculate though not dependant on the selected objective function. Heuristic algorithm is fast but dependant upon anticipated properties of the optimal solution. Hence, at change of the objective function it has to be changed. When the scheduling by genetic algorithms is solvable in a sufficiently short period of time, it is more appropriate from the practical point than the heuristic algorithm. The back-tracing algorithm usually does not provide a result in a feasible period of time.
topic optimization
scheduling
back-tracing
genetic algorithms
heuristic algorithm
url http://www.qip-journal.eu/index.php/QIP/article/view/35/23
work_keys_str_mv AT peterbober comparisonofdifferentapproachestothecuttingplanscheduling
_version_ 1716785744341630976