Chaos-based improved immune algorithm (CBIIA) for resource-constrained project scheduling problems

This paper introduces a novel meta-heuristic, the chaos-based improved immune algorithm (CBIIA), for solving resource-constrained project scheduling problems (RCPSP). In RCPSP the activities of a project have to be scheduled with the objective of minimizing total makespan subject to both temporal and resource constraints. The proposed CBIIA is based on the traits of an artificial immune system, chaotic generator and parallel mutation. CBIIA is different from the traditional immune algorithm in its initialization and hypermutation mechanism. Initialization in CBIIA is done by using chaotic generator (Logistic, Tent, and Sinusoidal) instead of conventional random number generator (RNG). The hypermutation is performed by parallel mutation (PM) operator rather than point mutation. Parallel mutation comprises two mutation strategies viz. Gaussian and Cauchy. Gaussian strategy is utilized for small step mutation and Cauchy strategy is for large step mutation. In order to demonstrate the efficacy of the proposed algorithm, Patterson's test suites are worked out. This study aims at developing an alternative and more efficient optimization methodology and opening the application of variants of artificial immune system for solving the RCPSP.

[1]  Manoj Kumar Tiwari,et al.  Determination of an optimal assembly sequence using the psychoclonal algorithm , 2005 .

[2]  Erik Demeulemeester,et al.  Resource-constrained project scheduling: A survey of recent developments , 1998, Comput. Oper. Res..

[3]  Manoj Kumar Tiwari,et al.  Fuzzy-based adaptive sample-sort simulated annealing for resource-constrained project scheduling , 2008 .

[4]  Kazuyuki Aihara,et al.  Chaotic simulated annealing by a neural network model with transient chaos , 1995, Neural Networks.

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

[6]  Concepción Maroto,et al.  A Robust Genetic Algorithm for Resource Allocation in Project Scheduling , 2001, Ann. Oper. Res..

[7]  Rema Padman,et al.  An integrated survey of deterministic project scheduling , 2001 .

[8]  C. Ribeiro,et al.  Essays and Surveys in Metaheuristics , 2002, Operations Research/Computer Science Interfaces Series.

[9]  Yanbin Yuan,et al.  A hybrid chaotic genetic algorithm for short-term hydro system scheduling , 2002, Math. Comput. Simul..

[10]  Toshihide Ibaraki,et al.  Formulation and Tabu Search Algorithm for the Resource Constrained Project Scheduling Problem , 2002 .

[11]  Bert De Reyck,et al.  A hybrid scatter search/electromagnetism meta-heuristic for project scheduling , 2006, Eur. J. Oper. Res..

[12]  Markus W. Schäffter,et al.  Scheduling with Forbidden Sets , 1997, Discret. Appl. Math..

[13]  Hartmut Schmeck,et al.  Ant colony optimization for resource-constrained project scheduling , 2000, IEEE Trans. Evol. Comput..

[14]  Luigi Fortuna,et al.  Chaotic sequences to improve the performance of evolutionary algorithms , 2003, IEEE Trans. Evol. Comput..

[15]  A. George,et al.  Receptor editing during affinity maturation. , 1999, Immunology today.

[16]  Leandro Nunes de Castro,et al.  Recent Developments In Biologically Inspired Computing , 2004 .

[17]  Krzysztof Fleszar,et al.  An evolutionary algorithm for resource-constrained project scheduling , 2002, IEEE Trans. Evol. Comput..

[18]  Sönke Hartmann,et al.  A self‐adapting genetic algorithm for project scheduling under resource constraints , 2002 .

[19]  D. Dasgupta Artificial Immune Systems and Their Applications , 1998, Springer Berlin Heidelberg.

[20]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[21]  G L Ada,et al.  The clonal-selection theory. , 1987, Scientific American.

[22]  Grzegorz Waligóra,et al.  Solving the discrete-continuous project scheduling problem via its discretization , 2000, Math. Methods Oper. Res..

[23]  Rainer Kolisch Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation , 1994 .

[24]  Arno Sprecher,et al.  Scheduling Resource-Constrained Projects Competitively at Modest Memory Requirements , 2000 .

[25]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[26]  Fabio A. González,et al.  An immunity-based technique to characterize intrusions in computer networks , 2002, IEEE Trans. Evol. Comput..

[27]  Francisco Ballestín,et al.  Justification and RCPSP: A technique that pays , 2005, Eur. J. Oper. Res..

[28]  Krzysztof Fleszar,et al.  Solving the resource-constrained project scheduling problem by a variable neighbourhood search , 2004, Eur. J. Oper. Res..

[29]  Robert Klein,et al.  Bidirectional planning: improving priority rule-based heuristics for scheduling resource-constrained projects , 2000, Eur. J. Oper. Res..

[30]  Manoj Kumar Tiwari,et al.  Modified immune algorithm for job selection and operation allocation problem in flexible manufacturing systems , 2008, Adv. Eng. Softw..

[31]  Francisco Ballestín,et al.  Resource-constrained project scheduling: A critical activity reordering heuristic , 2003, Eur. J. Oper. Res..