检索结果-内蒙古大学图书馆

software project scheduling under activity duration uncertainty

ANNALS OF OPERATIONS RESEARCH 2024年第1期338卷 477-512页

作者： Li, Hongbo Zhu, Hanyu Zheng, Linwen Xie, Fang Shanghai Univ Sch Management Shanghai 200444 Peoples R China Yantai Univ Sch Econ & Management Yantai 264005 Peoples R China

The main resources in software projects are human resources equipped with various skills, which makes software development a typical intelligence-intensive process. Therefore, effective human resource scheduling is indispensable for the success of software projects. The aim of software project scheduling is to assign the right employee to the right activity at the right time. Uncertainty is inevitable in software development, which further complicates the scheduling of projects. We investigate the software project scheduling problem with uncertain activity durations (SPSP-UAD) and aim at obtaining effective scheduling policies for the problem. We present and transform a scenario-based non-linear chance-constrained stochastic programming model into an equivalent linear programming model. To solve the NP-hard SPSP-UAD efficiently, we develop a hybrid meta-heuristic TLBO-GA that combines the teaching-learning-based optimization algorithm (TLBO) and the genetic algorithm (GA). Our TLBO-GA is also equipped with some problem-specific operators, such as population initialization, rows exchange and local search. We use simulation to evaluate the scheduling policies obtained by our algorithms. Extensive computational experiments are conducted to evaluate the performance of our TLBO-GA in comparison to the exact solver CPLEX and four existing meta-heuristic algorithms. The comparative results reveal the effectiveness and efficiency of our TLBO-GA. Our TLBO-GA provides an extensible and adaptive automated scheduling decision support tool for the software project manager in the complex and uncertain software development environment.

关键词： software project scheduling Uncertainty Stochastic programming Meta-heuristic algorithm

来源：评论

学校读者我要写书评

暂无评论

Evolutionary Algorithm for software project scheduling Considering Team Relationships

引用

IEEE ACCESS 2023年 11卷 43690-43706页

作者： Zhang, Jianhao Shen, Xiaoning Yao, Chengbin Nanjing Univ Informat Sci & Technol Sch Automat Nanjing 210044 Jiangsu Peoples R China Jiangsu Key Lab Big Data Anal Technol Nanjing 210044 Jiangsu Peoples R China Jiangsu Engn Res Ctr Meteorol Energy Using & Contr Nanjing 210044 Jiangsu Peoples R China Jiangsu Collaborat Innovat Ctr Atmospher Environm Nanjing 210044 Jiangsu Peoples R China

Human relationships have a great impact on the software development process. Meanwhile, project development may require the acquisition of new skills that employees have not yet acquired due to changes in customer requirements. However, such factors are seldom incorporated into software project scheduling problem. To address this, a novel mathematical model considering the team relationships is established for software project scheduling problem. This model introduces the communication cost factor of each employee, and analyses its quantitative connections with changes in human relationships and the growth of skill proficiency respectively. In addition, a selection mechanism for external employees is designed to meet new skill requirements. To solve the model, an improved bi-population discrete evolutionary algorithm based on information feedback is proposed. The heuristic information of "employee suitability" is utilized in initialization to obtain better initial individuals. The feedback mechanism based on "evolutionary quality" is applied to provide an effective strategy for adaptive tuning of subpopulation size. The selection probabilities of distinct crossover operators are adjusted according to the "improved quantity" to increase crossover efficiency. Moreover, an enhanced local search strategy based on the "degree of team cooperation" and the "improved quantity" is developed. Experimental results show that by considering human relationships under different communication cost factors, the duration and cost of the project are significantly reduced. Compared with four state-of-the-art algorithms, the scheduling performance of the proposed algorithm can be improved by 10.6374% to 25.8566%.

关键词： software Task analysis Costs software algorithms Evolutionary computation Optimization Optimal scheduling software project scheduling communication cost human relationship information feedback evolutionary algorithm

来源：评论

学校读者我要写书评

暂无评论

Solving software project scheduling problems with ant colony optimization

引用

COMPUTERS & OPERATIONS RESEARCH 2013年第1期40卷 33-46页

作者： Xiao, Jing Ao, Xian-Ting Tang, Yong S China Normal Univ Sch Comp Sci Guangzhou Guangdong Peoples R China Sun Yat Sen Univ Dept Comp Sci Guangzhou 510275 Guangdong Peoples R China

software project scheduling problem (SPSP) is one of the important and challenging problems faced by the software project managers in the highly competitive software industry. As the problem is becoming an NP-hard problem with the increasing numbers of employees and tasks, only a few algorithms exist and the performance is still not satisfying. To design an effective algorithm for SPSP, this paper proposes an ant colony optimization (ACO) approach which is called ACS-SPSP algorithm. Since a task in software projects involves several employees, in this paper, by splitting tasks and distributing dedications of employees to task nodes we get the construction graph for ACO. Six domain-based heuristics are designed to consider the factors of task efforts, allocated dedications of employees and task importance. Among these heuristic strategies, the heuristic of allocated dedications of employees to other tasks performs well. ACS-SPSP is compared with a genetic algorithm to solve the SPSP on 30 random instances. Experimental results show that the proposed algorithm is promising and can obtain higher hit rates with more accuracy compared to the previous genetic algorithm solution. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： scheduling Automatic software management software project scheduling Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

The software project scheduling problem: A scalability analysis of multi-objective metaheuristics

引用

APPLIED SOFT COMPUTING 2014年第0期15卷 136-148页

作者： Luna, Francisco Gonzalez-Alvarez, David L. Chicano, Francisco Vega-Rodriguez, Miguel A. Univ Extremadura Dept Ingn Sistemas Informat & Telemat Merida Spain Univ Extremadura Dept Tecnol Comp & Comunicac Caceres Spain Univ Malaga Dept Lenguajes & Ciencias Comp E-29071 Malaga Spain

Computer aided techniques for scheduling software projects are a crucial step in the software development process within the highly competitive software industry. The software project scheduling (SPS) problem relates to the decision of who does what during a software project lifetime, thus involving mainly both people-intensive activities and human resources. Two major conflicting goals arise when scheduling a software project: reducing both its cost and duration. A multi-objective approach is therefore the natural way of facing the SPS problem. As companies are getting involved in larger and larger software projects, there is an actual need of algorithms that are able to deal with the tremendous search spaces imposed. In this paper, we analyze the scalability of eight multi-objective algorithms when they are applied to the SPS problem using instances of increasing size. The algorithms are classical algorithms from the literature (NSGA-II, PAES, and SPEA2) and recent proposals (DEPT, MOCell, MOABC, MO-FA, and GDE3). From the experimentation conducted, the results suggest that PAES is the algorithm with the best scalability features. (C) 2013 Elsevier B.V. All rights reserved.

关键词： software project scheduling Scalability analysis Multi objective optimization

来源：评论

学校读者我要写书评

暂无评论

A Novel Multi-Objective Evolutionary Algorithm to Address Turnover in the software project scheduling Problem Based on Best Fit Skills Criterion

引用

IEEE ACCESS 2023年 11卷 89742-89756页

作者： Nigar, Natasha Shahzad, Muhammad Kashif Islam, Shahid Oki, Olukayode Lukose, Jose Manappattukunnel Univ Engn & Technol Lahore RCET Dept Comp Sci Lahore 54890 Pakistan Power Informat Technol Co PITC Goverment Pakistan Power Div Minist Energy Lahore 54000 Pakistan Walter Sisulu Univ Dept Informat Technol ZA-5117 Mthatha South Africa

As a typical scheduling problem, the software project scheduling (SPS) under uncertain and dynamic events has gathered attention of academic researchers and practitioners because it causes tangible and intangible loss and will also influence the project schedule and cost if not addressed in time. In this paper, a SPS model based on skills acquired by employees and required by tasks criterion is proposed to tackle the issue of 'employee turnover' along with novel multi-objective evolutionary optimization algorithm to handle such dynamic events by employing the domain knowledge for population initialization. This is critical for the success of a software project as when an employee leaves, the project is rescheduled with remaining resources to assess if the project can be completed on time and under budget;otherwise, an alternative resource is hired. The proposed model and algorithm are evaluated on 18 dynamic benchmark and 6 real-world problem instances. The experimental results indicate that if existing employees are reassigned to the tasks, the project cost and duration increases on average 22% and 4% respectively. However, hiring new employees with recommended skills and proficiency based on proposed approach provides 9% decrease in project cost with no increase in duration and 15% decrease in cost against 11% referenced increase in project duration, in comparison to classical rescheduling results. The results demonstrate that proposed model and algorithm handles dynamic event effectively and help in identifying the right set of skills for hiring of an alternate resource while optimizing project duration and cost.

关键词： software Heuristic algorithms Costs Dynamic scheduling Uncertainty Schedules Task analysis software development management Metaheuristics software project scheduling employee turnover meta-heuristics multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

Firework-based software project scheduling method considering the learning and forgetting effect

引用

SOFT COMPUTING 2019年第13期23卷 5019-5034页

作者： Guo, Yinan Ji, Jianjiao Ji, Junhua Gong, Dunwei Cheng, Jian Shen, Xiaoning China Univ Min & Technol Xuzhou Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Nanjing Jiangsu Peoples R China

The learning and forgetting ability, as the inherent characteristics of the employees, have a great impact on the software development process. By using the idea of WLC learning and VRVF forgetting models, an novel learning and forgetting model is constructed for software project scheduling problem to measure the dynamic skill levels. Taking the cost and duration as the optimization objectives, corresponding software project scheduling model considering the learning and forgetting effect is formed. The improved multi-objective firework algorithm with a novel encoding scheme is present. The crossover-explosion operator is introduced to enhance the information exchange between the better sparks or fireworks. A novel reservation strategy with two archives is proposed to avoid the ineffective search around the local optimum. Experimental results indicate that the learning ability plays a positive role on the optimal scheduling schemes and the forgetting effect is the opposite. The duration and cost of the project are inversely proportional to the learning coefficient and directly proportional to forgetting coefficient. By comparing the scheduling schemes from NSGA-II and original FA, the proposed method shows the better scheduling performances.

关键词： Firework algorithm Learning effect Forgetting effect software project scheduling

来源：评论

学校读者我要写书评

暂无评论

A Hybrid PSO-ACO Algorithm to Facilitate software project scheduling

引用

INTERNATIONAL JOURNAL OF E-COLLABORATION 2022年第2期18卷 1-12页

作者： Joe, Praveen I. R. Malathy, E. M. Aishwarya, S. Akila, R. Akshaya, A. Vellore Inst Technol Comp Sci & Engn Chennai Campus Chennai Tamil Nadu India Sri Sivasubramaniya Nadar Coll Engn Informat Technol Chennai Tamil Nadu India Zoho Corp Pvt Ltd Chengalpattu Tamil Nadu India CSS Corp Pvt Ltd Chennai Tamil Nadu India Anna Univ Madras Tamil Nadu India

While tailoring software applications, in the present day scenario, there is a huge demand for cost-effective products;however, it is challenging for the developers to make a trade-off between cost and quality as well as between quality and time. Late delivery, sometimes, has become inevitable due to the reasons like improper time schedules, technical issues, changing customer requirements, miscommunication amongst team members, failure to analyse the risks involved, and underrating of resources like man cost, power, effort, etc. Here in this work an attempt has been made to study the advantages of swarm-based optimization techniques over traditional optimization approaches and thereby employ them efficiently to schedule projects. A hybrid PSO-ACO algorithm is proposed for scheduling purposes. The nuances of natural swarm cultures are appropriately incorporated into the software scheduling scenario, and the results are recorded and reported. It is observed that the readings are passible and are benchmarked through relevant measures of quality.

关键词： Ant Colony Optimization Particle Swarm Optimization software project scheduling Swarm Intelligence

来源：评论

学校读者我要写书评

暂无评论

Impacts of synergies on software project scheduling

引用

ANNALS OF OPERATIONS RESEARCH 2022年第2期312卷 883-908页

作者： Kosztyan, Zsolt T. Bogdany, Eszter Szalkai, Istvan Kurbucz, Marcell T. Univ Pannonia Dept Quantitat Methods 10 Egyet St H-8200 Veszprem Hungary Inst Adv Studies iASK 14 Chernel St H-9730 Koszeg Hungary MTA PE Budapest Ranking Res Grp 10 Egyet St H-8200 Veszprem Hungary Univ Pannonia Dept Management 10 Egyet St H-8200 Veszprem Hungary Univ Pannonia Dept Math 10 Egyet St H-8200 Veszprem Hungary Wigner Res Ctr Phys Dept Computat Sci 29-33 Konkoly Thege Miklos St H-1121 Budapest Hungary

The adequate allocation of human resources is one of the most important success factors in software projects. Although project teams can be regarded as complex systems in which a team's performance is highly influenced by the interdependencies among team members, the allocation methods applied to date have focused only on individual skills and consider project teams as units of isolated workers. The existing software project scheduling problem (SPSP) is extended to (1) consider different skills and efficiencies of employees and (2) examine the pairwise synergies between them, as well as to (3) handle the flexible structure of the project that is used in flexible management, such as agile project management. To better understand the impact of synergies on the project's cost, the solutions of the traditional and extended SPSP versions are analyzed and compared on the generated project networks. The results show not only that this factor has a highly significant impact but also that the project cost strongly depends on the structural parameters of the synergy network (e.g., topology, network size and degree centrality). Among these parameters, a low degree of centrality and some topologies, most notably star and circular networks, obtained the highest reduction in the projects' total cost.

关键词： software project scheduling Staffing Synergy network Social network Genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Empirical Study of Multi-objective Ant Colony Optimization to software project scheduling Problems 15

Empirical Study of Multi-objective Ant Colony Optimization t...

引用

17th Genetic and Evolutionary Computation Conference (GECCO)

作者： Xiao, Jing Gao, Mei-Ling Huang, Min-Mei S China Normal Univ Sch Comp Sci Guangzhou 510631 Guangdong Peoples R China S China Normal Univ Sch Publ Adm Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781450334723

The software project scheduling Problem (SPSP) focuses on the management of software engineers and tasks in a software project so as to complete the tasks with a minimal cost and duration. It's becoming more and more important and challenging with the rapid development of software industry. In this paper, we employ a Multi-objective Evolutionary Algorithm using Decomposition and Ant Colony (MOEA/D-ACO) to solve the SPSP. To the best of our knowledge, it is the first application of Multi-objective Ant Colony Optimization (MOACO) to SPSP. Two heuristics capable of guiding the algorithm to search better in the SPSP model are examined. Experiments are conducted on a set of 36 publicly available instances. The results are compared with the implementation of another multi-objective evolutionary algorithm called NSGA-II for SPSP. MOEA/D-ACO does not outperform NSGA-II for most of complex instances in terms of Pareto Front. But MOEA/D-ACO can obtain solutions with much less time for all instances in our experiments and it outperforms NSGA-II with less duration for most of test instances. The performance may be improved with tuning of the algorithm such as incorporating more heuristic information or using other MOACO algorithms, which deserve further investigation.

关键词： software project scheduling Multi-objective Optimization Ant Colony Optimization Automatic software project Management MOEA/D NSGA-II

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Approach to Quantitative software project scheduling Within Agile Frameworks

引用

project MANAGEMENT JOURNAL 2014年第3期45卷 35-45页

作者： Jahr, Michael European Univ Appl Sci EUFH Dept Ind Management Neuss Germany

In this article we focus on the quantitative project scheduling problem in IT companies that apply the agile management philosophy and Scrum, in particular. We combine mathematical programming with an agile project flow using a modified multi-mode resource constrained project scheduling model for software projects (MRCPSSP). The proposed approach can be used to generate schedules as benchmarks for agile development iterations. Computational experiments based on real project data indicate that this approach significantly reduces the project cycle time. The approach can be a useful addition to agile project management, especially for software projects with predefined deadlines and budgets.

关键词： software project scheduling quantitative project management agile software development Scrum

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：