The Use of Metaheuristics to Software Project Scheduling Problem

This paper provides an overview of Software Project Scheduling problem as a combinatorial optimization problem. Since its inception by Alba, there have been multiple models to solve this problem. Metaheuristics provide high-level strategies capable of solving these problems efficiently. A set of metaheuristics used to solve this problem is presented, showing the resolution structure and its application. Among these we can find Simulated Annealing, Variable Neighborhood Search, Genetic Algorithms, and Ant Colony Optimization.

[1]  William E. Hart,et al.  Recent Advances in Memetic Algorithms , 2008 .

[2]  David Taniar,et al.  Computational Science and Its Applications - ICCSA 2009, International Conference, Seoul, Korea, June 29-July 2, 2009, Proceedings, Part I , 2009, ICCSA.

[3]  Thomas Stützle,et al.  Ant Colony Optimization Theory , 2004 .

[4]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[5]  Juraj Hromkovic,et al.  Algorithmics for hard problems - introduction to combinatorial optimization, randomization, approximation, and heuristics , 2001 .

[6]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[7]  Broderick Crawford,et al.  Ants Can Schedule Software Projects , 2013, HCI.

[8]  David Taniar,et al.  Computational Science and Its Applications – ICCSA 2013 , 2013, Lecture Notes in Computer Science.

[9]  Max Bramer,et al.  Artificial Intelligence in Theory and Practice II , 2009 .

[10]  Pablo Moscato,et al.  On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms , 1989 .

[11]  Gündüz Ulusoy,et al.  A survey on the resource-constrained project scheduling problem , 1995 .

[12]  Broderick Crawford,et al.  Hypercube FrameWork for ACO applied to timetabling , 2006, IFIP AI.

[13]  Tao Zhang,et al.  Genetic Algorithms for Project Management , 2001, Ann. Softw. Eng..

[14]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[15]  Sanjay Misra,et al.  Apply Agile Method for Improving the Efficiency of Software Development Project at VNG Company , 2013, ICCSA.

[16]  Enrique Alba,et al.  Software project management with GAs , 2007, Inf. Sci..

[17]  Yong Tang,et al.  Solving software project scheduling problems with ant colony optimization , 2013, Comput. Oper. Res..

[18]  Enrique Alba,et al.  Análisis y diseño de algoritmos genéticos paralelos distribuidos , 2011 .

[19]  El-Ghazali Talbi,et al.  Metaheuristics - From Design to Implementation , 2009 .

[20]  Nimo Parra,et al.  Metaheuristics to solve the software project scheduling problem , 2012, 2012 XXXVIII Conferencia Latinoamericana En Informatica (CLEI).

[21]  Michel Gendreau,et al.  Metaheuristics in Combinatorial Optimization , 2022 .

[22]  Winston Khoon Guan Seah,et al.  A performance study on synchronicity and neighborhood size in particle swarm optimization , 2013, Soft Comput..

[23]  Francisco Chicano.  Metaheurísticas e ingeniería del software , 2011 .

[24]  Amit Mishra,et al.  People management in software industry: the key to success , 2010, SOEN.

[25]  Luca Maria Gambardella,et al.  A survey on metaheuristics for stochastic combinatorial optimization , 2009, Natural Computing.

[26]  Grzegorz Waligóra,et al.  Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models , 2005, Eur. J. Oper. Res..

[27]  Pierre Hansen,et al.  Les Cahiers Du Gerad Variable Neighborhood Search Methods , 1999 .

[28]  Sanjay Misra,et al.  Effective Project Leadership in Computer Science and Engineering , 2009, ICCSA.