Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm

For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order en...

Full description

Saved in:
Bibliographic Details
Main Authors: Mengqi Liu, Miyuan Shan, Juan Wu
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/652135
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849468614892060672
author Mengqi Liu
Miyuan Shan
Juan Wu
author_facet Mengqi Liu
Miyuan Shan
Juan Wu
author_sort Mengqi Liu
collection DOAJ
description For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment.
format Article
id doaj-art-f29082b5a7b547c9a20b45f3c0cd3f15
institution Kabale University
issn 2356-6140
1537-744X
language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-f29082b5a7b547c9a20b45f3c0cd3f152025-08-20T03:25:47ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/652135652135Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm AlgorithmMengqi Liu0Miyuan Shan1Juan Wu2School of Business Administration, Hunan University, Changsha, Hunan 410082, ChinaSchool of Business Administration, Hunan University, Changsha, Hunan 410082, ChinaSchool of Business Administration, Hunan University, Changsha, Hunan 410082, ChinaFor most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment.http://dx.doi.org/10.1155/2014/652135
spellingShingle Mengqi Liu
Miyuan Shan
Juan Wu
Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
The Scientific World Journal
title Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
title_full Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
title_fullStr Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
title_full_unstemmed Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
title_short Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
title_sort multiple r d projects scheduling optimization with improved particle swarm algorithm
url http://dx.doi.org/10.1155/2014/652135
work_keys_str_mv AT mengqiliu multiplerdprojectsschedulingoptimizationwithimprovedparticleswarmalgorithm
AT miyuanshan multiplerdprojectsschedulingoptimizationwithimprovedparticleswarmalgorithm
AT juanwu multiplerdprojectsschedulingoptimizationwithimprovedparticleswarmalgorithm