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software project scheduling problem in the context of search-based software engineering: A systematic review

JOURNAL OF SYSTEMS AND software 2019年第0期155卷 43-56页

作者： Rezende, Allan Vinicius Silva, Leila Britto, Andre Amaral, Rodrigo Fed Univ Sergipe UFS Comp Sci Dept BR-49100000 Sao Cristovao Brazil

This work provides a systematic literature review of the software project scheduling problem, in the context of search-based software engineering, and summarizes the main models, techniques, search algorithms and evaluation criteria applied to solve this problem. We also discuss trends and research opportunities. Our keyword search found 438 papers, published in the last 20 years. After considering the inclusion and exclusion criteria and performing the snowballing procedure, we have analyzed 37 primary studies. The results show the predominance of the use of evolutionary algorithms. The static model, in which the scheduling is performed once during the project, is considered in the majority of the papers. Synthetic instances are commonly used to validate the heuristic and hypervolume and execution time are the mostly applied evaluating criteria. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Search-based software engineering software project scheduling problem Systematic review

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A Max-Min Ant System algorithm to solve the software project scheduling problem

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EXPERT SYSTEMS WITH APPLICATIONS 2014年第15期41卷 6634-6645页

作者： Crawford, Broderick Soto, Ricardo Johnson, Franklin Monfroy, Eric Paredes, Fernando Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ Finis Terrae Santiago Chile Univ Playa Ancha Valparaiso Chile Univ Autonoma Chile Santiago Chile Univ Nantes LINA CNRS Nantes France Univ Diego Portales Escuela Ingn Ind Santiago Chile

The software project scheduling problem is a specific project scheduling problem present in many industrial and academic areas. This problem consists in making the appropriate worker-task assignment in a software project so the cost and duration of the project are minimized. We present the design of a Max-Min Ant System algorithm using the Hyper-Cube framework to solve it. This framework improves the performance of the algorithm. We illustrate experimental results and compare with other techniques demonstrating the feasibility and robustness of the approach, while reaching competitive solutions. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Ant Colony Optimization project management software engineering software project scheduling problem

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A survey on the software project scheduling problem

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2018年 202卷 145-161页

作者： Angel Vega-Velazquez, Miguel Garcia-Najera, Abel Cervantes, Humberto Univ Autonoma Metropolitana Iztapalapa San Rafael Atlixco 186 Cdmx 09340 DF Mexico Univ Autonoma Metropolitana Cuajimalpa Ave Vasco de Quiroga 4871 Col Santa Fe Cuajimalpa 05348 Cdmx Mexico

Creating a plan for a software project is a recurring activity in software development organizations that plays a critical role in the project success. When creating a plan for a project, these organizations must deal with the problem of allocating resources to tasks in the project. Because of its importance, there has been considerable research focused on finding ways to solve this problem, which is known as the software project scheduling problem (SPSP). Solving this problem usually focuses on creating a schedule for a project with minimal duration and cost. As part of our work, we have found only one survey about the SPSP, however it focuses primarily on the methods used to solve it, while the rest of the surveys focus primarily on other scheduling problems such as the Resource-Constrained project scheduling problem. In this paper, we present a survey of the current research focused on solving the SPSP. For this survey, we have analyzed and classified a number of research studies considering a set of criteria that include: the model used to represent the problem, the optimization goals, the optimization techniques used to solve the problem, the methodology used to evaluate the different approaches, and the main results. From our analysis, we produce a set of general observations and provide suggestions that we believe can be useful for future research in this field.

关键词： project scheduling software project scheduling problem Survey Planning model Optimization algorithms

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Metaheuristics to solve the software project scheduling problem

Metaheuristics to solve the software project scheduling prob...

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38th Latin America Conference on Informatics (CLEI)

作者： Parra, Nimo Carolina, Dahyana Salazar, Amaya Edgar, Jhon Univ Tachira UNET LCAR San Cristobal Estado Tachira Venezuela

ISBN: (纸本)9781467307932;9781467307949

This document describes the software project scheduling problem as a combinatorial optimization problem trough the project scheduling problem (PSP). The authors represent the problem as a single-objective problem, which is solved through a group of metaheuristics, including an hybrid strategy that allows to schedule software projects, by minimizing either cost or duration. The metaheuristics implemented were validated with 18 instances of software projects with different number of developers, tasks and skills.

关键词： software project scheduling problem Metaheuristics Hybrid Strategy

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Comparative Analysis of Ant Colony Extended and Mix-Min Ant System in software project scheduling problem

Comparative Analysis of Ant Colony Extended and Mix-Min Ant ...

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International Workshop on Big Data and Information Security (IWBIS)

作者： Rachman, Valdi Ma'sum, M. Anwar Univ Indonesia Fac Comp Sci Depok Indonesia

ISBN: (纸本)9781538620380

software project scheduling problem (SPSP) is one of project scheduling problem which is classified as NP-Hard problem. In 2014, variation of Ant Colony Optimization (ACO) algorithms was successfully developed. The algorithm is Max-Min Ant System (MMAS) that proposed to solve SPSP. In 2012, there is variation of ACO named Ant Colony Extended (ACE) developed for Travelling Salesman problem and it shows better performance than well-known ACO algorithms: MMAS and Ant Colony System (ACS). However, there is no research about ACE's performance in SPSP where MMAS is successfully applied. In this paper, ACE and MMAS algorithm were compared in SPSP. The experiment result shows that ACE has better performance than MMAS for SPSP. The performance is indicated by fitness value of the algorithms

关键词： Ant Colony Optimization project management software project scheduling problem

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An Alternative Solution to the software project scheduling problem 5th

An Alternative Solution to the Software Project Scheduling P...

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5th Computer Science On-line Conference (CSOC)

作者： Crawford, Broderick Soto, Ricardo Astorga, Gino Olguin, Eduardo Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ San Sebastian Providencia Chile Univ Cent Chile Santiago Chile Univ Autonoma Chile Temuco Chile Univ Cient Sur Lima Peru

ISBN: (纸本)9783319336251;9783319336237

Due to the competitiveness of the software industry a more stressful tasks for software project managers allocation of the human resources to the different tasks that perform the project. This is not an easy task and it is necessary that is computationally supported since every day projects are larger and these should be developed in the shortest time and possible costs. We propose to use a constructive metaheuristics called Intelligent Water Drops. In this paper the result are compared with another constructive metaheuristics obtaining promising performance.

关键词： Intelligent Water Drops project management software project scheduling problem

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A New Approach to Solve the software project scheduling problem Based on Max-Min Ant System 3

A New Approach to Solve the Software Project Scheduling Prob...

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3rd Computer Science On-line Conference (CSOC)

作者： Crawford, Broderick Soto, Ricardo Johnson, Franklin Monfroy, Eric Paredes, Fernando Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ Playa Ancha Valparaiso Chile Univ Finis Terrae Santiago Chile Univ Autonoma Chile Temuco Chile Univ Nantes CNRS LINA Nantes France Univ Diego Portales Santiago Chile

ISBN: (纸本)9783319067407

This paper presents a new approach to solve the software project scheduling problem. This problem is NP-hard and consists in finding a workertask schedule that minimizes cost and duration for the whole project, so that task precedence and resource constraints are satisfied. Such a problem is solved with an Ant Colony Optimization algorithm by using the Max-Min Ant System and the Hyper-Cube framework. We illustrate experimental results and compare with other techniques demonstrating the feasibility and robustness of the approach, while reaching competitive solutions.

关键词： software engineering software project scheduling problem project management Ant colony optimization Max-Min ant system

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Solving the software project scheduling problem Using Intelligent Water Drops

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TEHNICKI VJESNIK-TECHNICAL GAZETTE 2018年第2期25卷 350-357页

作者： Crawford, Broderick Soto, Ricardo Astorga, Gino Castro, Carlos Paredes, Fernando Misra, Sanjay Rubio, Jose-Miguel Pontificia Univ Catolica Valparaiso Ave Brasil 2950 Valparaiso Chile Univ Valparaiso Prat 856 Valparaiso Chile Univ Tecn Federico Santa Maria Ave Espana 1680 Valparaiso Chile Univ Diego Portales Escuela Ingn Ind Manuel Rodriguez Sur 415 Santiago Chile Covenant Univ Dept Comp & Informat Sci Ota Nigeria Atilim Univ TR-06836 Ankara Turkey Univ Tecnol Chile INACAP Brown Norte 260 Nunoa Chile

Within the category of project scheduling problems, there is a specific problem within the software industry referred to as the software project scheduling problem. The problem consists in the correct allocation of employees to the different tasks that make up a software project, bearing in mind time and cost restraints. To achieve this goal, the present work first uses metaheuristic intelligent water drops illustrating;this is a recent stochastic swarm-based method increasingly used for solving optimization problems. Finally, the results and comparisons with experiments performed with other techniques are presented, demonstrating the solidity of the approach presented.

关键词： combinational optimization computational intelligence intelligent water drops metaheuristics software project scheduling problem

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iMOPSE: a library for bicriteria optimization in Multi-Skill Resource-Constrained project scheduling problem

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SOFT COMPUTING 2019年第10期23卷 3397-3410页

作者： Myszkowski, Pawel B. Laszczyk, Maciej Nikulin, Ivan Skowronski, Marek Wroclaw Univ Sci & Technol Collect Intelligence Dept Wyb Wyspianskiego 27 PL-50370 Wroclaw Poland

This paper presents a software library as a research and educational tool for Multi-Skill Resource-Constrained scheduling problem. The following useful tools have been implemented in Java: instance Generator, solution validator, solution visualizer and example solvers: Greedy algorithm and Genetic Algorithm. All tools are supported by iMOPSE dataset which consists of 36 instances and additional 'small' 6 instances for educational purpose. In the paper, three test studies are described: (1) educational use of 6 'small' instances, (2) optimization of cost or duration of a schedule, and (3) simple bicritieria optimization of cost/duration of a final schedule. All described tools/examples are freely published on iMOPSE homepage.

关键词： Optimization scheduling MS-RCPSP software project scheduling problem Experimental design Library Benchmark dataset Java

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A software project Management problem Solved by Firefly Algorithm 1

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16th International Conference on Computational Science and Its Applications (ICCSA)

作者： Crawford, Broderick Soto, Ricardo Johnson, Franklin Misra, Sanjay Olguin, Eduardo Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ Cent Chile Santiago Chile Univ Cient Sur Lima Peru Univ Autonoma Chile Santiago Chile Univ Playa Ancha Valparaiso Chile Covenant Univ Ogun Nigeria Univ San Sebastian Fac Ingn & Tecnol Bellavista 7 Santiago 8420524 Chile

ISBN: (数字)9783319420929

ISBN: (纸本)9783319420929

In software project management there are several problems to deal, one of those is the software project scheduling problem (SPSP). This problem requires to assign a set of resources to tasks for a given project, trying to decrease the duration and cost of the whole project. The workers and their skills are the main resources in the project. In this paper we present the SPSP as a combinatorial optimization problem and a novel approach to solve SPSP by a Firefly algorithm. Firefly algorithm is a new metaheuristic based on the behaviour of the firefly. We present the design of the resolution model to solve the SPSP using an algorithm of fireflies and we illustrate some experimental results in order to demonstrate the viability and soundness of our approach.

关键词： Firefly algorithm Metaheuristic software project scheduling problem project management

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