A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production

The steelmaking and continuous-casting (SCC) process in integrated iron and steel enterprises can be described as two stages: the upstream stage and downstream stage. Raw materials are transformed into molten steel in the upstream stage, while the downstream stage is responsible for transforming mol...

Full description

Bibliographic Details
Main Authors: Hongtao Hu, Yiwei Wu, Tingsong Wang
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2018/8073648
id doaj-8811310c445b45beb46ba782953bf14e
record_format Article
spelling doaj-8811310c445b45beb46ba782953bf14e2020-11-25T00:44:11ZengHindawi LimitedDiscrete Dynamics in Nature and Society1026-02261607-887X2018-01-01201810.1155/2018/80736488073648A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting ProductionHongtao Hu0Yiwei Wu1Tingsong Wang2College of Logistics Engineering, Shanghai Maritime University, Shanghai 201306, ChinaSchool of Management, Shanghai University, Shanghai 200444, ChinaSchool of Economics and Management, Wuhan University, Wuhan 430072, ChinaThe steelmaking and continuous-casting (SCC) process in integrated iron and steel enterprises can be described as two stages: the upstream stage and downstream stage. Raw materials are transformed into molten steel in the upstream stage, while the downstream stage is responsible for transforming molten steel which is released at regular intervals and has a limited time for being turned into slabs. This article focuses on the task assignment problem in the downstream stage within the given information resulting from the upstream stage. This problem is formulated as a nonlinear mixed-integer programming model aimed at minimizing total tardiness within the resource constraints and time windows constraints for the tasks. An improved solution algorithm based on particle swam optimization is developed to efficiently solve the proposed model. Finally, computational experiments are implemented to evaluate the performance of the solution algorithm in terms of solution quality and computational time.http://dx.doi.org/10.1155/2018/8073648
collection DOAJ
language English
format Article
sources DOAJ
author Hongtao Hu
Yiwei Wu
Tingsong Wang
spellingShingle Hongtao Hu
Yiwei Wu
Tingsong Wang
A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production
Discrete Dynamics in Nature and Society
author_facet Hongtao Hu
Yiwei Wu
Tingsong Wang
author_sort Hongtao Hu
title A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production
title_short A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production
title_full A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production
title_fullStr A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production
title_full_unstemmed A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production
title_sort metaheuristic method for the task assignment problem in continuous-casting production
publisher Hindawi Limited
series Discrete Dynamics in Nature and Society
issn 1026-0226
1607-887X
publishDate 2018-01-01
description The steelmaking and continuous-casting (SCC) process in integrated iron and steel enterprises can be described as two stages: the upstream stage and downstream stage. Raw materials are transformed into molten steel in the upstream stage, while the downstream stage is responsible for transforming molten steel which is released at regular intervals and has a limited time for being turned into slabs. This article focuses on the task assignment problem in the downstream stage within the given information resulting from the upstream stage. This problem is formulated as a nonlinear mixed-integer programming model aimed at minimizing total tardiness within the resource constraints and time windows constraints for the tasks. An improved solution algorithm based on particle swam optimization is developed to efficiently solve the proposed model. Finally, computational experiments are implemented to evaluate the performance of the solution algorithm in terms of solution quality and computational time.
url http://dx.doi.org/10.1155/2018/8073648
work_keys_str_mv AT hongtaohu ametaheuristicmethodforthetaskassignmentproblemincontinuouscastingproduction
AT yiweiwu ametaheuristicmethodforthetaskassignmentproblemincontinuouscastingproduction
AT tingsongwang ametaheuristicmethodforthetaskassignmentproblemincontinuouscastingproduction
AT hongtaohu metaheuristicmethodforthetaskassignmentproblemincontinuouscastingproduction
AT yiweiwu metaheuristicmethodforthetaskassignmentproblemincontinuouscastingproduction
AT tingsongwang metaheuristicmethodforthetaskassignmentproblemincontinuouscastingproduction
_version_ 1725275860734312448