Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-26T18:53:38.440Z Has data issue: false hasContentIssue false

An improved ant algorithm for Multi-mode Resource ConstrainedProject Scheduling Problem

Published online by Cambridge University Press:  11 July 2014

Peng Wuliang
Affiliation:
School of Economic and Management, Shenyang Ligong University, 110159 Shenyang, P.R. China. . peng-wuliang@163.com
Huang Min
Affiliation:
College of Information Science and Engineering, Northeastern University, 110819 Shenyang, P.R. China
Hao Yongping
Affiliation:
Laboratory of Advanced Manufacture and Equipment of Liaoning, Shenyang Ligong University, 110159 Shenyang, P.R. China
Get access

Abstract

Many real-world scheduling problems can be modeled as Multi-mode Resource ConstrainedProject Scheduling Problems (MRCPSP). However, the MRCPSP is a strong NP-hard problem andvery difficult to be solved. The purpose of this research is to investigate a moreefficient alternative based on ant algorithm to solve MRCPSP. To enhance the generalityalong with efficiency of the algorithm, the rule pool is designed to manage numerouspriority rules for MRCPSP. Each ant is provided with an independent thread and endowedwith the learning ability to dynamically select the excellent priority rules. In addition,all the ants in the ant algorithm have the prejudgment ability to avoid infeasible routesbased on the branch and bound method. The algorithm is tested on the well-known benchmarkinstances in PSPLIB. The computational results validate the effectiveness of the proposedalgorithm.

Type
Research Article
Copyright
© EDP Sciences, ROADEF, SMAI 2014

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abdallah, H., Emara, H.M., Dorrah, H.T. and Bahgat, A., Using Ant Colony Optimization algorithm for solving project management problems. Exp. Syst. Appl. 36 (1999) 1000410015. Google Scholar
Alcaraz, J., Maroto, C. and Ruiz, R., Solving the multi-mode resource-constrained project scheduling problem with genetic algorithms. J. Oper. Res. Soc. 54 (2003) 614626. Google Scholar
Bautista, J. and Pereira, J., Ant colonies for the RCPS problem. Lect. Notes in Comput. Sci. 2504 (2002) 257268. Google Scholar
Boctor, F.F., Heuristics for scheduling projects with resource restrictions and several resource-duration modes. Int. J. Prod. Res. 31 (1993) 25472558. Google Scholar
Boctor, F.F., A new and efficient heuristic for scheduling projects with resource restrictions and multiple execution modes. Eur. J. Oper. Res. 90 (1996) 349361. Google Scholar
Bouleimen, K. and Lecocq, H., A new efficient simulated annealing algorithm for the resource constrained project scheduling problem. Eur. J. Oper. Res. 149 (2003) 268281. Google Scholar
Buddhakulsomsiri, J. and Kim, D.S., Priority rule-based heuristic for multi-mode resource-constrained project scheduling problems with resource vacations and activity splitting. Eur. J. Oper. Res. 178 (2007) 374-390. Google Scholar
Daniel, M., Martin, M. and Hartmut, S., Ant colony optimization for resource-constrained project scheduling. IEEE Trans. Evol. Comput. 6 (2002) 333346. Google Scholar
E. Demeulemeester and W. Herroelen, Project scheduling: A research handbook. Kluwer Academic Publishers (2002).
Dorigo, M., Maniezzo, V. and Colorni, A., Ant system: Optimization by a colony of cooperating agents. IEEE Trans. Syst. Man Cybern 26 (1996) 2941. Google ScholarPubMed
Drexl, A. and Grünewald, J., Nonpreemptive multi-mode resource-constrained project scheduling. IIE Trans. 25 (1993) 7481. Google Scholar
S.E. Elmaghraby, Activity networks: project planning and control by network models. Wiley, New York (1997).
Hartmann, S., Project scheduling with multiple modes: a genetic algorithm. Annal. Oper. Res. 102 (2001) 111135. Google Scholar
Hartmann, S. and Drexl, A., Project scheduling with multiple modes: a comparison of exact algorithms. Networks 32 (1998) 283297. Google Scholar
Hartmann, S. and Kolish, R., Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem. Eur. J. Oper. Res. 127 (2000) 394407. Google Scholar
Jarboui, B., Damak, N. and Siarry, P., A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems. Appl. Math. Comput. 195 (2008) 299308. Google Scholar
Kolisch, R., Serial and parallel resource-constrained project scheduling methods revisitedtheory and computation. Eur. J. Oper. Res. 90 (1996) 320333. Google Scholar
Kolisch, R. and Drexl, A., Local search for nonpreemptive multi-mode resource-constrained project scheduling. IIE Trans. 29 (1997) 987999. Google Scholar
Kolisch, R. and Sprecher, A., PSPLIB-A project scheduling problem library. Eur. J. Oper. Res. 96 (1997) 205216. Google Scholar
Lova, A., Tormos, P., Cervantes, M. and Barber, F., An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes. Int. J. Prod. Econ.s 117 (2009) 302316. Google Scholar
Merkle, D. and Middendorf, M., An ant algorithm with a new pheromone evaluation rule for total tardiness problems. Lect. Notes Comput. Sci. 1803 (2000) 287296. Google Scholar
Ozdamar, L., A genetic algorithm approach to a general category project scheduling problem. IEEE Trans. Syst. Man Cybern. 29 (1999) 4459. Google Scholar
Peteghem, V.V. and Vanhoucke, M., A genetic algorithm for the preemptive and non-preemtive multi-mode resource-constrained project scheduling problem. Eur. J. Oper. Res. 201 (2009) 409418. Google Scholar
Peteghem, V.V. and Vanhoucke, M., An artificial immune system for the multi-mode resource-constrained project scheduling problem. Evol. Comput. Comb. Optim. 5482 (2009) 8596. Google Scholar
Ranjbar, M., De Reyck, B., B. and Kianfar, F., A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling. Eur. J. Oper. Res. 193 (2008) 3548. Google Scholar
Slowinski, R., Soniewicki, B. and Weglarz, J., DSS for multiobjective project scheduling subject to multiple-category resource constraints. Eur. J. Oper. Res. 79 (1994) 220229. Google Scholar
Sprecher, A., Hartmann, S. and Drexl, A., An exact algorithm for the project scheduling with multiple modes. OR Spektrum 19 (1997) 195203. Google Scholar
Sprecher, A. and Drexl, A., Multi-mode resource-constrained project scheduling by a simple, general and powerful sequencing algorithm. Eur. J. Oper. Res. 107 (1998) 431450. Google Scholar
Tseng, L.Y. and Chen, S.C., A hybrid meta-heuristic for the resource-constrained project scheduling problem. Eur. J. Oper. Res. 175 (2006) 707721. Google Scholar
Wang, C., et al., An efficient hybrid algorithm for resource-constrained project scheduling. Inform. Sci. 180 (2010) 10311039. Google Scholar
Zhang, H., Li, H. and Tam, C.M., Particle swarm optimization for resource-constrained project scheduling. Int. J. Project Manag. 24 (2006) 8392. Google Scholar
Zhu, G., Bard, J. and Tu, G., A Branch-and-Cut Procedure for the Multimode Resource-Constrained Project-Scheduling Problem. J. Comput. 18 (2006) 377390. Google Scholar