Theoretical and practical fundamentals for multi-objective optimisation in resource-constrained project scheduling problems

Computers and Operations Research

Volumn 38, Issue 1, 2011, Pages 51-62

  Ballestín, Francisco ^a   Blanco, Rosa ^a  

^a PUBLIC UNIVERSITY OF NAVARRE   (Spain)

Author keywords

Heuristic algorithms; Multi objective; Resource constrained project scheduling

Indexed keywords

CONSTRAINED OPTIMIZATION; HEURISTIC METHODS; MULTIOBJECTIVE OPTIMIZATION; SCHEDULING;

COMPUTATIONAL RESULTS; HEURISTIC PROCEDURES; META HEURISTIC ALGORITHM; MULTI OBJECTIVE; MULTI-OBJECTIVE PROBLEM; OBJECTIVE FUNCTIONS; RESOURCE CONSTRAINED PROJECT SCHEDULING; RESOURCE-CONSTRAINED PROJECT SCHEDULING PROBLEM;

HEURISTIC ALGORITHMS;

EID: 78049425864     PISSN: 03050548     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cor.2010.02.004     Document Type: Conference Paper

References (54)

1. P. Brucker, A. Drexl, R. Mhring, K. Neumann, and E. Pesch Resource-constrained project scheduling: notation, classification, models and methods European Journal of Operational Research 112 1999 3 41
2. W. Herroelen, B. De Reyck, and E. Demeulemeester Resource-constrained project scheduling: a survey of recent developments Computers and Operations Research 25 1998 279 302
3. R. Kolisch, and R. Padman An integrated survey of deterministic project scheduling Omega 49 2001 249 272
4. L. zdamar, and G. Ulusoy A survey on the resource-constrained project scheduling problem IIE Transactions 27 1995 574 586
5. E. Demeulemeester, and W. Herroelen Project schedulinga research handbook 2002 Kluwer Academic Publishers Boston
6. K. Neumann, C. Schwindt, and J. Zimmermann Project scheduling with time windows and scarce resources 2002 Springer
7. M. Ehrgott, and X. Gandibleux Approximative solution methods for multiobjective combinatorial optimization TOP 12 1 2004 1 88
8. P. Hansen Bicriterion path problems G. Fandel, T. Galé, Multiple criteria decision making theory and application. Lecture notes in economics and mathematical systems vol. 177 1979 Springer Berlin, Heidelberg, NewYork 109 127
9. M. Ehrgott Approximation algorithms for combinatorial multicriteria optimization problems International Transactions in Operational Research 7 2000 5 31
10. V.A. Emelichev, and V.A. Perepelitsa Complexity of vector optimization problems on graphs Optimization 22 1991 903 918
11. P. Serafini Some considerations about computational complexity for multi objective combinatorial problems J. Jahn, W. Krabs, Recent advances and historical development of vector optimization. Lecture notes in economics and mathematical systems vol. 294 1986 Springer Berlin, Heidelberg, New York 222 232
12. M.R. Garey, and D.S. Johnson Computers and intractabilitya guide to the theory of NP-completeness 1979 Freeman San Francisco, CA
13. L.G. Valiant, and V.V. Vazirani NP is as easy as detecting unique solutions Theoretical Computer Science 47 1986 85 93
14. R. Slowinski Multiobjective network scheduling under multiple-category resource constraints R. Slowinski, J. Weglarz, Advances in project scheduling 1989 Elsevier Amsterdam 151 167
15. M.A. Al-Fawzan, and M. Haouari A bi-objective model for robust resource-constrained project scheduling International Journal of Production Economics 96 2005 175 187
16. Hwang CL, Masud AS. Multi-objective decision making, methods and applications. A state of the art survey. Lecture notes in economics and mathematical systems, Springer-Verlag, Berlin; 1979.
17. Horn J. Multicriteria decision making. In: Back T, Fogel DB, Michalewicz Z, editors. Handbook of evolutionary computation. 97/1, F1.9, IOP Publishing Ltd. and Oxford University Press; 1997.
18. Zitzler E. Evolutionary algorithms for multiobjective optimization: methods and applications. Ph.D. thesis, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland; 1999.
19. R. Slowinski Multiobjective network scheduling with efficient use of renewable and nonrenewable resources European Journal of Operational Research 7 1981 265 273
20. Słowiński R, Wglarz J. An interactive algorithm for multiobjective precedence and resource constrained scheduling problems. In: Proceedings of the 8 World Congress on Project Management INTERNET'85. North-Holland, Amsterdam/New York/Oxford, 1985. p. 86673.
21. R. Sowiski, B. Soniewiclu, and J. Wglarz DSS for multiobjective project scheduling European Journal of Operational Research 79 2 1994 220 229
22. Hapke M, Jaszkiewicz A, Slowinski R. Fuzzy project scheduling with multiple criteria. Fuzzy systems. In: Proceedings of the sixth IEEE international conference, Barcelona, Spain; 1997. p. 127782.
23. M. Hapke, and R. Slowinski Fuzzy set approach to multi-objective and multi-mode project scheduling under uncertainty R. Slowinski, M. Hapke, Scheduling under fuzziness 2000 Physica-Verlag Heidelberg 197 221 Chapter 9
24. Pan H, Yeh C-H. A metaheuristic approach to fuzzy project scheduling. Lecture notes in computer science, vol. 2773/2003. Springer, 2003. p. 10811087.
25. M. Hapke, A. Jaszkiewicz, and R. Slowinski Interactive analysis of multiple-criteria project scheduling problems European Journal of Operational Research 107 1998 315 324
26. Nabrzyski J, Wglarz J. On an expert system with tabu search for multiobjective project scheduling. In: Proceedings of INRIA/IEEE symposium on emerging technologies and factory automation III. 1995. p. 8794.
27. J. Nabrzyski, and J. Wglarz Knowledge-based multiobjective project scheduling problems J. Wglarz, Project scheduling: recent models, algorithms and applications 1999 Kluwer Boston 383 413 [chapter 17]
28. A. Viana, and J.P. de Sousa Using metaheuristics in multiobjective resource constraints project scheduling European Journal of Operational Research 120 2000 359 374
29. C. Schwindt, and J. Zimmermann Parametrische Optimierung als Instrument zur Bewertung von Investitionsprojekten Zeitschrift fr Betriebswirtschaft 72 2002 593 617
30. B. Abbasi, S. Shadrokh, and J. Arkat Bi-objective resource-constrained project scheduling with robustness and makespan criteria Applied Mathematics and Computation 180 2006 146 152
31. R. Kolisch, and S. Hartmann Experimental investigation of heuristics for resource-constrained project scheduling: an update European Journal of Operational Research 174 2006 23 37
32. Bui, L., Abbass, H., Essam, D., Green, D. Performance analysis of evolutionary multi-objective optimization methods in noisy environments. In: Proceedings of the 8th Asia Pacific symposium on intelligent and evolutionary systems. 2004. p. 2939.
33. Zitzler E, Laumanns M, Thiele L. Sped: improving the strength Pareto evolutionary algorithm. Technical Report 103, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, Switzerland, 2001.
34. K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan A fast elitist nondominated sorting genetic algorithm for multi-objective optimization: NSGA-II M. Schoenauer, Parallel problem solving from nature (PPSN VI) 2000 Springer Berlin, Germany 849 858
35. R.K. Suresh, and K.M. Mohanasundaram Pareto archived simulated annealing for job shop scheduling with multiple objectives International Journal on Advanced Manufacturing Technology 29 2006 184 196
36. P. Czyzak, and A. Jaszkiewicz Metaheuristic technique for solving multiobjective investment planning problem Control and Cybernetics 25 1 1996 177 187
37. S. Hartmann A competitive genetic algorithm for resource-constrained project scheduling Naval Research Logistics 45 1998 733 750
38. V. Valls, F. Ballestín, and S. Quintanilla Justification and RCPSP: a technique that pays European Journal of Operational Research 165 2005 375 386
39. A. Drexl Scheduling of project networks by job assignment Management Science 37 1991 1590 1602
40. S. Hartmann A self-adapting genetic algorithm for project scheduling under resource constraints Naval Research Logistics 49 2002 433 448
41. Kochetov Y, Stolyar A. Evolutionary local search with variable neighborhood for the resource constrained project scheduling problem. In: Proceedings of the third international workshop of computer science and information technologies, Russia, 2003.
42. D.S. Yamashita, V.A. Armentano, and M. Laguna Scatter search for project scheduling with resource availability cost European Journal of Operational Research 169 2006 623 637
43. S. Shadrokh, and F. Kianfar A genetic algorithm for resource investment project scheduling problem, tardiness permitted with penalty European Journal of Operational Research 181 2007 86 101
44. E. Zitzler, L. Thiele, M. Laumanns, C. Fonseca, and V. Grunert da Fonseca Performance assessment of multiobjective optimizers: an analysis and review IEEE Transactions on Evolutionary Computation 7 2 2003 117 132
45. S. Sayin Measuring the quality of discrete representations of efficient sets in multiple objective mathematical programming Mathematical Programming 87 3 2000 543 560
46. Van Veldhuizen D. Multiobjective evolutionary algorithms: classifications, analyses, and new innovations. Ph.D. thesis, School of Engineering of the Air Force Institute of Technology, 1999.
47. Fleischer M. The measure of Pareto optima. Applications to multiobjective metaheuristics. In: Fonseca C, Fleming P, Zitzler E, Deb K, Thiele L, editors. Evolutionary multi-criterion optimization. Second international conference, EMO 2003, Lecture notes in computer science, vol. 2632. 2003. p. 51933.
48. R. Kolisch, A. Sprecher, and A. Drexl Characterization and generation of a general class of resource-constrained project scheduling problems Management Science 41 1995 1693 1703
49. F. Ballestín, V. Valls, and S. Quintanilla Due dates and RCPSP J. Jzefowska, J. Weglarz, Perspectives in modern project scheduling 2006 Springer [Chapter 4]
50. S. Hartmann, and R. Kolisch Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem European Journal of Operational Research 127 2000 394 407
51. R.A. Fisher Statistical methods for research workers 1925 Oliver and Boyd Edinburgh
52. W.J. Dixon, and A.M. Mood The statistical sign test Journal of the American Statistical Association 41 1946 557 566
53. Czyzak P, Jaszkiewicz A. Pareto simulated annealinga metaheuristic technique for multiple-objective combinatorial optimization. Journal of Multi-Criteria Analysis 1998;7:3447.
54. Zitzler E, Thiele L. Multiobjective optimization using evolutionary algorithmsa comparative case study. In: Ebeling W, Rechenberg I, Schwefel H-P, Voigt H-M, Editors. Parallel problem solving from naturePPSN V, LNCS vol. 2632/1998. Heidelberg: Springer-Verlag; 1998.