Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System Conversion

The line-seru conversion is usually used to improve productivity, especially in volatile business environment. Due to the simplicity, most researches focused on line-pure seru system conversion. We summarize the two existing models (i.e., a biobjective model and a single-objective model) of line-pur...

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Main Authors: Wei Sun, Qianqian Li, Chunhui Huo, Yang Yu, Ke Ma
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2016/9748378
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spelling doaj-92e03c2e432b4e059a52d600b3a62d9c2020-11-24T22:39:11ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/97483789748378Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System ConversionWei Sun0Qianqian Li1Chunhui Huo2Yang Yu3Ke Ma4Business School, Liaoning University, Shenyang 110316, ChinaBusiness School, Liaoning University, Shenyang 110316, ChinaBusiness School, Liaoning University, Shenyang 110316, ChinaInstitute of Systems Engineering, State Key Laboratory of Synthetic Automation for Process Industries, Northeastern University, Shenyang 110819, ChinaInstitute of Systems Engineering, State Key Laboratory of Synthetic Automation for Process Industries, Northeastern University, Shenyang 110819, ChinaThe line-seru conversion is usually used to improve productivity, especially in volatile business environment. Due to the simplicity, most researches focused on line-pure seru system conversion. We summarize the two existing models (i.e., a biobjective model and a single-objective model) of line-pure system conversion and formulate the three other usually used single-objective models in an integrated framework by combining evaluated performances and constraints. Subsequently, we analyze the solution space features of line-pure seru system conversion by dividing the whole solution space into several subspaces according to the number of serus. We focus on investigating the features between Cmax (and TLH) and subspaces. Thirdly, according to the distinct features between Cmax (and TLH) and subspaces, we propose four effective algorithms to solve the four single-objective models, respectively. Finally, we evaluate the computational performance of the developed algorithms by comparing with enumeration based on extensive experiments.http://dx.doi.org/10.1155/2016/9748378
collection DOAJ
language English
format Article
sources DOAJ
author Wei Sun
Qianqian Li
Chunhui Huo
Yang Yu
Ke Ma
spellingShingle Wei Sun
Qianqian Li
Chunhui Huo
Yang Yu
Ke Ma
Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System Conversion
Mathematical Problems in Engineering
author_facet Wei Sun
Qianqian Li
Chunhui Huo
Yang Yu
Ke Ma
author_sort Wei Sun
title Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System Conversion
title_short Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System Conversion
title_full Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System Conversion
title_fullStr Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System Conversion
title_full_unstemmed Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System Conversion
title_sort formulations, features of solution space, and algorithms for line-pure seru system conversion
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2016-01-01
description The line-seru conversion is usually used to improve productivity, especially in volatile business environment. Due to the simplicity, most researches focused on line-pure seru system conversion. We summarize the two existing models (i.e., a biobjective model and a single-objective model) of line-pure system conversion and formulate the three other usually used single-objective models in an integrated framework by combining evaluated performances and constraints. Subsequently, we analyze the solution space features of line-pure seru system conversion by dividing the whole solution space into several subspaces according to the number of serus. We focus on investigating the features between Cmax (and TLH) and subspaces. Thirdly, according to the distinct features between Cmax (and TLH) and subspaces, we propose four effective algorithms to solve the four single-objective models, respectively. Finally, we evaluate the computational performance of the developed algorithms by comparing with enumeration based on extensive experiments.
url http://dx.doi.org/10.1155/2016/9748378
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