Document Type: Original Article

Authors

1 Imam Hossein University of Technology, Tehran, Iran.

2 Department of Industrial Engineering, Faculty of Engineering, Semnan University, Semnan, Iran.

3 Islamic Azad University of South Tehran, Tehran, Iran.

4 Department of Industrial Engineering, Eyvanakey University, Eyvanakey, Iran.

Abstract

Today's competitive conditions have caused the projects to be carried out in the least possible time with limited resources. Therefore, managing and scheduling a project is a necessity for the project. The timing of a project is to specify a sequence of times for a series of related activities. According to their priority and their latency, so that between the time the project is completed and the total cost is balanced. Given the balance between time and cost, and to achieve these goals, there are several options that should be considered among existing options and ultimately the best option to perform activities to complete the project. In this research, a mathematical model of project scheduling with multiple goals based on cost patterns and consideration of resource constraints is presented, and this problem is considered as a problem for NP-hard issues in family hybrid optimization. GA، PSO and SA Meta-heuristic algorithms are used to solve the proposed model in project scheduling and the results are compared with each other.

Keywords

Babaee Tirkolaee, E., Alinaghian, M., Bakhshi Sasi, M.M., and Seyyed Esfahani, M., (2016). ''Solving a robust capacitated arc routing problem using a hybrid simulated annealing algorithm A waste collection application'', Journal of Industrial Engineering and Management Studies (JIEMS), Vol. 3 , No. 1, pp. 61-76.

Baradaran, S., Ghomi, S. F., Mobini, M., and Hashemin, S. S., (2010). ''A hybrid scatter search approach for resource-constrained project scheduling problem in PERT-type networks'', Advances in Engineering Software, Vol. 41, No7-8, pp. 966-975.

Birjandi, A., and Mousavi, S. M., (2019). ''Fuzzy resource-constrained project scheduling with multiple routes: A heuristic solution'', Automation in Construction, Vol. 100, pp. 84-102.

Chen, W. N., Zhang, J., Liu, O., and Liu, H. L., (2010). ''A Monte-Carlo ant colony system for scheduling multi-mode projects with uncertainties to optimize cash flows''. In IEEE Congress on Evolutionary Computation, pp. 1-8.

Chen, W. N., and Zhang, J., (2012). ''Scheduling multi-mode projects under uncertainty to optimize cash flows: a Monte Carlo ant colony system approach''. Journal of computer science and technology, Vol. 27, No. 5, pp. 950-965.

Daneshpayeh, H., (2011). ''Project schedule under the uncertainty of activities time using a Meta-heuristic algorithm (Case study: Part of the Project Activities of Gas Condensate Refinery in Bandar Abbas) '', M.S Thesis, Imam Hossein University. Tehran, Pp.102-104. (In Persian).

Fakhrzad, M.B., and Alidoosti, Z., (2018). ''A realistic perishability inventory management for location inventory-routing problem based on Genetic Algorithm'', Journal of Industrial Engineering and Management Studies (JIEMS), Vol.5, No.1, pp. 106-121.

Hassan-Pour, H. A., Mosadegh-Khah, M., and Tavakkoli-Moghaddam, R., (2009). ''Solving a multi-objective multi-depot stochastic location-routing problem by a hybrid simulated annealing algorithm'', Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 223, No. 8, pp. 1045-1054.

Haji Akhundi, A., Tavakoli, Gh., Akhavan, P., and Logoogi, M., (2015). ''Solving the Project Scheduling Problem with the Purpose of Minimizing Project Execution Time with Resource Constraints with Froggy's Fractional Algorithm'', Industrial Management Magazine, Faculty of Humanities, Islamic Azad University, Sanandaj Branch, Vol. 40, pp. 112-97.

Hassanzadeh, R.,  Mahdavi, I., and  Mahdavi-Amiri, N., (2015). ''Particle swarm optimization for a bi-objective web-based convergent product networks'', Journal of Industrial Engineering and Management Studies (JIEMS), Vol. 2, No. 1, pp. 41-50.

Hosseininasab, S.M., Shetab-Boushehri, S.N., Hejazi, S.R., and Hadi Karimi, H., (2018). ''A multi-objective integrated model for selecting, scheduling, and budgeting road construction projects'', European Journal of Operational Research, Vol. 271, No. 1, pp. 262-277.

Jia, Q., and Seo, Y., (2013). ''An improved particle swarm optimization for the resource-constrained project scheduling problem'', The International Journal of Advanced Manufacturing Technology, Vol. 67, No. 9-12, pp. 2627-2638.

Kima, K.W., Genb, M., and Yamazaki, G., (2003). ''Hybrid genetic algorithm with fuzzy logic for resource-constrained project scheduling''. Applied Soft Computing, Vol. 2, pp. 174–188.

Kwan, W. K., Mitsuo, G. and Genji, Y., (2003). ''Hybrid genetic algorithm with fuzzy logic for resource-constrained project scheduling'', Applied Soft Computing, Vol. 2, No. 3, pp.174–188.

Luong, D.L., and Ario, O., (2008). ''Fuzzy critical chain method for project scheduling under resource constraints and uncertainty'', International Journal of Project Management, Vol. 26, pp. 688–698.

Molavi, F., and Rezaee Nik, E., (2016). ''A stochastic model for project selection and scheduling problem'', Journal of Industrial Engineering and Management Studies (JIEMS), Vol. 3, No. 1, pp. 77-88.

Maghsoudlou,H.,  Afshar-Nadjafi, B., and AkhavanNiaki, S.T., (2016). ''A multi-objective invasive weeds optimization algorithm for solving multi-skill multi-mode resource constrained project scheduling problem'', Computers & Chemical Engineering. Vol. 88, No. 8, pp. 157-169. 

Min-Yuan, C., Hsing-Chih, T., and Chih-Lung, L., (2009). ''Artificial intelligence approaches to achieve strategic control over project cash flows'', Automation in Construction, Vol. 18, pp. 386–393.

Mika, M., Waligora, G., and Weglarz, G., (2005). ''Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models'', European Journal of Operational Research, Vol. 164, pp. 639-668.

Najafi, A.A., Akhavan Niaki, S.T., and Shahsavar, M., (2009). ''A parameter-tuned genetic algorithm for the resource investment problem with discounted cash flows and generalized precedence relations'', Computers & Operations Research, Vol. 36, pp. 2994–3001.

Pellerin, R., Perrier, N., and Berthaut, F., (2020). ''A survey of hybrid metaheuristics for the resource-constrained project scheduling problem'', European Journal of Operational Research, Vol. 280, No. 2, pp. 395-416.

Rahman, H. F., Chakrabortty, R. K., and Ryan, M. J., (2020). ''Memetic algorithm for solving resource constrained project scheduling problems'', Automation in Construction, Vol. 111, pp. 103052.

Rajeevan, M., and Nagavinothini, R., (2015). ''Time Optimization for Resource-Constrained Project Scheduling Using Meta-heuristic Approach'', International Journal of Science, Engineering and Technology Research (IJSETR). Vol. 4, No. 3, pp. 606-609.

Ritwik, A., and Paul, G., (2013). ''A Heuristic Algorithm for Resource Constrained Project Scheduling Problem with Discounted Cash Flows'', International Journal of Innovative Technology and Exploring Engineering (IJITEE), Vol. 3, pp. 2278-3075.

Rifat, S., and Önder Halis, B., (2012). ''A hybrid genetic algorithm for the discrete time–cost trade-off problem'', Expert Systems with Applications, Vol. 39, pp. 11428–11434.

Rahimi Nejad, Saman, (2014). ''Presented a mathematical model for the location of mobile communication antennas, a case study company-wide spring'', M.Sc. Thesis, University of Imam Hussein, MA, pp. 1-150.

Sonmez, R., and Bettemir, Ö.H., (2012). ''A hybrid genetic algorithm for the discrete time-cost trade-off problem'', Expert Systems with Applications, Vol. 39, pp. 11428–11434.

Shah Mohammadi, A., and Kazemi, M., (2015). 8th International Iranian Enemy Conference on Operations Research, Ferdowsi University of Mashhad, Iran, pp. 1-2. 

Shams, M., Jafarzadeh Afshari, A., and Khakbaz. A., (2017). ''Integrated modeling and solving the resource allocation problem and task scheduling in the cloud computing environment'', Journal of Industrial Engineering and Management Studies (JIEMS), Vol.4, No.1, pp. 69-89.

Sadeghi, M., Niloofar, P., Ziaee, M., and Mojaradi, Zahra, (2017). ''An innovative algorithm for planning a scheduling healthcare units with the aim of reducing the length of stay for patients (Case study: Cardiac SurgeryWard of Razavi Hospital of Mashhad)'', Journal of Industrial Engineering and Management Studies (JIEMS), Vol.4, No.1, pp. 90-104.

Stiti, C., and Driss, O. B., (2019). ''`A new approach for the multi-site resource-constrained project scheduling problem'', Procedia Computer Science, Vol. 164, pp. 478-484.

Tareghian, H.R., and Taheri, S.H., (2007). ''A solution procedure for the discrete time-cost and quality tradeoff problem using electromagnetic scatter search'', Applied Mathematics and Computation, Vol. 190, pp. 1136–1145.

Wang, H. W., Lin, J. R., and Zhang, J. P. (2020). ''Work package-based information modeling for resource-constrained scheduling of construction projects'', Automation in Construction, Vol. 109, pp.102958.

Yang, B., Geunes, J., and O’Brien, W.J., (2004). ''A heuristic approach for minimizing weighted tardiness and overtime costs in single resource scheduling'', Computers & Operations Research, Vol. 31, pp. 1273–1301.

Zareei, M., Hassan-Pour, H.A., and Mosadegh-Khah, M., (2014). ''Time-Cost Tradeoff for Optimizing Contractor NPV by Cost Payment and Resource Constraints Using NSGA-II Algorithm (Case StudyBandar Abbas Gas Condensate Refinery Project)'', Journal of Mathematics and Computer Science, Vol. 12, No. 1, pp. 1-98.

Zandieh, M.., Asgari Tehrani, M.M., (2014). ''A cloud-based simulated annealing algorithm for order acceptance problem with weighted tardiness penalties in permutation flow shop scheduling'', Journal of Industrial Engineering and Management Studies (JIEMS), Vol. 1, No. 1, pp. 1-9.