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Impacts of different objective functions on resource leveling in Line-of-Balance scheduling

  • Construction Management
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Abstract

This study investigates the impacts of using different objective functions in leveling resources in schedules established by using Line-Of-Balance (LOB) methodology. A genetic algorithm-based model that considers different objective functions was used for leveling resources in LOB schedules. This model uses the principles of “optimum crew size” and “natural rhythm” that assume that the highest productivity can be achieved as long as an activity is performed in a unit of production by one or multiple crews of optimum size. Therefore, one needs to change the number of crews employed to shift the start times of an activity forwards or backwards at different units of production. The total project duration, the duration of an activity in any unit and the precedence relationships between activities remain the same during this procedure. Two LOB schedules are established for a pipeline project and are used to investigate the impacts of using different objective functions for resource leveling in LOB. It was observed that the objective functions provided the same optimal resource distribution. However, prudent schedulers should consider all ten objective functions because the distribution of resources depends on the number of activities, the float of each activity, and the precedence relationships between activities.

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References

  • Ahuja, H. N. (1976). Construction performance control by networks, John Wiley and Sons, New York, USA.

    Google Scholar 

  • Alghazi, A., Elazouni, A., and Selim, S. (2013). “Improved genetic algorithm for finance-based scheduling.” Journal of Computing in Civil Engineering, Vol. 27, No. 4, pp. 379–394, DOI: 10.1061/(ASCE)CP.1943-5487.0000227.

    Article  Google Scholar 

  • Ammar, M. A. and Elbeltagi, E. (2001). “Algorithm for determining controlling path considering resource continuity.” Journal of Computing in Civil Engineering, Vol. 15, No. 4, pp. 292–298, DOI: 10.1061/(ASCE)0887-3801(2001)15:4(292).

    Article  Google Scholar 

  • Arditi, D. and Albulak, M. Z. (1986). “Line-of-balance scheduling in pavement construction.” Journal of Construction Engineering and Management, Vol. 112, No. 3, pp. 411–424, DOI: 10.1061/(ASCE)0733-9364(1986)112:3(411).

    Article  Google Scholar 

  • Arditi, D., Tokdemir, O. B., and Kangsuk, S. (2001). “Effect of learning on line of balance scheduling.” International Journal of Project Management, Vol. 19, No. 5, pp. 265–277, DOI: 10.1016/S0263-7863(99)00079-4.

    Article  Google Scholar 

  • Arditi, D., Tokdemir, O. B., and Kangsuk, S. (2002). “Challenges in Line-of-Balance Scheduling.” Journal of Construction Engineering and Management, Vol. 128, No. 6, pp. 545–556, DOI: 10.1061/(ASCE)0733-9364(2002)128:6(545).

    Article  Google Scholar 

  • Burgess, A. R. and Killebrew, J. B. (1962). “Variation in activity level on a cyclical arrow diagram.” Journal of Industrial Engineering, Vol. 13, No. 2, pp. 76–83.

    Google Scholar 

  • Chen, P. H. and Weng, H. (2009). “A two-phase GA model for resourceconstrained project scheduling.” Automation in Construction, Vol. 18, No. 4, pp. 485–498, DOI: 10.1016/j.autcon.2008.11.003.

    Article  Google Scholar 

  • Christodoulou, S. (2010). “Scheduling resource-constrained projects with ant colony optimization artificial agents.” Journal of Computing in Civil Engineering, Vol. 24, No. 1, pp. 45–55, DOI: 10.1061/(ASCE)0887-3801(2010)24:1(45).

    Article  Google Scholar 

  • Christodoulou, S., Ellinas, G., and Aslani, P. (2009). “Entropy–based scheduling of resource-constrained construction projects.” Automation in Construction, Vol. 18, No. 7, pp. 919–928, DOI: 10.1016/j.autcon.2009.04.007.

    Article  Google Scholar 

  • Damci, A. and Polat, G. (2014). “Impacts of different objective functions on resource leveling in construction projects.” Journal of Civil Engineering and Management, Vol. 20, No. 4, pp. 537–547, DOI: 10.3846/13923730.2013.801909.

    Article  Google Scholar 

  • Damci, A., Arditi, D., and Polat, G. (2013a). “Resource leveling in lineof-balance scheduling.” Computer-Aided Civil and Infrastructure Engineering, Vol. 28, No. 9, pp. 679–692, DOI: 10.1111/mice.12038.

    Article  Google Scholar 

  • Damci, A., Arditi, D., and Polat, G. (2013b). “Multi-resource leveling in line-of-balance scheduling.” Journal of Construction Engineering and Management, Vol. 139, No. 9, pp. 1108–1116, DOI: 10.1061/(ASCE)CO.1943-7862.0000716.

    Article  Google Scholar 

  • Doulabi, S. H. H., Seifi, A., and Shariat, S. Y. (2011). “Efficient hybrid genetic algorithm for resource leveling via activity splitting.” Journal of Construction Engineering and Management, Vol. 137, No. 2, pp. 137–146, DOI: 10.1061/(ASCE)CO.1943-7862.0000261.

    Article  Google Scholar 

  • Dubey, A. (1993).Resource leveling and linear scheduling, MSc. Thesis, Department of Civil Engineering, The University of British Columbia, Vancouver, Canada.

    Google Scholar 

  • Easa, S. M. (1989). “Resource leveling in construction by optimization.” Journal of Construction Engineering and Management, Vol. 115, No. 2, pp. 302–316, DOI: 10.1061/(ASCE)0733-9364(1989)115:2(302).

    Article  Google Scholar 

  • El-Rayes, K. and Jun, D. H. (2009). “Optimizing resource leveling in construction projects.” Journal of Construction Engineering and Management, Vol. 135, No. 11, pp. 1172–1180, DOI: 10.1061/(ASCE)CO.1943-7862.0000097.

    Article  Google Scholar 

  • Elwany, M. H., Korish, I. E., Barakat, M. A., and Hafez, S. M. (1998). “Resource smoothing in repetitive projects.” Computers and Industrial Engineering, Vol. 35, Nos. 3–4, pp. 415–418, DOI: 10.1016/S0360-8352(98)00122-3.

    Article  Google Scholar 

  • Georgy, M. E. (2008). “Evolutionary resource scheduler for linear projects.” Automation in Construction, Vol. 17, No. 5, pp. 573–583, DOI: 10.1016/j.autcon.2007.10.005.

    Article  Google Scholar 

  • Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning, Addison-Wesley, Reading, UK.

    Google Scholar 

  • Goldberg, D. E. and Kuo, C. H. (1987). “Genetic algorithms in pipeline optimization.” Journal of Computing in Civil Engineering, Vol. 1, No. 2, pp. 128–141, DOI: 10.1061/(ASCE)0887-3801(1987)1:2(128).

    Article  Google Scholar 

  • Hariga, M. and El-Sayegh, S. M. (2011). “Cost optimization model for the multiresource leveling problem with allowed activity splitting.” Journal of Construction Engineering and Management, Vol. 137, No. 1, pp. 56–64, DOI: 10.1061/(ASCE)CO.1943-7862.0000251.

    Article  Google Scholar 

  • Harris, R. B. (1978). Precedence and arrow networking techniques for construction, John Wiley and Sons, New York, USA.

    Google Scholar 

  • Harris, R. B. (1990). “Packing Method for Resource Leveling (PACK).” Journal of Construction Engineering and Management, Vol. 116, No. 2, pp. 331–350, DOI: 10.1061/(ASCE)0733-9364(1990)116:2(331).

    Article  Google Scholar 

  • Hegazy, T. (1999). “Optimization of resource allocation and leveling using genetic algorithms.” Journal of Construction Engineering and Management, Vol. 125, No. 3, pp. 167–175, DOI: 10.1061/(ASCE)0733-9364(1999)125:3(167).

    Article  Google Scholar 

  • Hegazy, T. and Ersahin, T. (2001). “Simplified spreadsheet solutions. II: Overall schedule optimization.” Journal of Construction Engineering and Management, No. 127, No. 6, pp. 469–475, DOI: 10.1061/(ASCE)0733-9364(2001)127:6(469).

    Article  Google Scholar 

  • Hegazy, T. and Kassab, M. (2003). “Resource optimization using combined simulation and genetic algorithms.” Journal of Construction Engineering and Management, Vol. 129, No. 6, pp. 698–705, DOI: 10.1061/(ASCE)0733-9364(2003)129:6(698).

    Article  Google Scholar 

  • Hiyassat, M. A. S. (2000). “Modification of minimum moment approach in resource leveling.” Journal of Construction Engineering and Management, Vol. 126, No. 4, pp. 278–284, DOI: 10.1061/(ASCE)0733-9364(2000)126:4(278).

    Article  Google Scholar 

  • Hiyassat, M. A. S. (2001). “Applying modified minimum moment method to multiple resource leveling.” Journal of Construction Engineering and Management, Vol. 127, No. 3, pp. 192–198, DOI: 10.1061/(ASCE)0733-9364(2001)127:3(192).

    Article  Google Scholar 

  • Leu, S. S., Yang, C. H., and Huang, J. C. (2000). “Resource leveling in construction by genetic algorithm-based optimization and its decision support system application.” Automation in Construction, Vol. 10, No. 1, pp. 27–41, DOI: 10.1016/S0926-5805(99)00011-4.

    Article  Google Scholar 

  • Lucko, G. (2011). “Integrating efficient resource optimization and linear schedule analysis with singularity functions.” Journal of Construction Engineering and Management, Vol. 137, No. 1, pp. 45–55, DOI: 10.1061/(ASCE)CO.1943-7862.0000244.

    Article  Google Scholar 

  • Lumsden, P. (1968). The line-of-balance method, Pergamon Press Limited, London, UK.

    Google Scholar 

  • Mattila, K. G. and Abraham, D. M. (1998). “Resource leveling of linear schedules: Using integer linear programming.” Journal of Construction Engineering and Management, Vol. 124, No. 3, pp. 232–244, DOI: 10.1061/(ASCE)0733-9364(1998)124:3(232).

    Article  Google Scholar 

  • Moder, J. J., Phillips, C. R., and Davis, E. W. (1983). Project management with CPM, PERT and Precedence Programming, Van Nostrand Reinhold, New York, USA.

    Google Scholar 

  • Negnevitsky, M. (2002). Artificial intelligence-A guide to intelligent systems, Pearson Education, London, UK.

    Google Scholar 

  • Popescu, C. M. (1976). How to use C.P.M. in practice, Part II — resources, University of Texas at Austin, USA.

    Google Scholar 

  • Risk Solver Platform (2011). User guide, Frontline Systems Inc., NV.

    Google Scholar 

  • Senouci, A. B. and Eldin, N. N. (2004). “Use of genetic algorithms in resource scheduling of construction projects.” Journal of Construction Engineering and Management, Vol. 130, No. 6, pp. 869–877, DOI: 10.1061/(ASCE)0733-9364(2004)130:6(869).

    Article  Google Scholar 

  • Son, J. and Skibniewski, M. J. (1999). “Multiheuristic approach for resource leveling problem in construction engineering: Hybrid approach.” Journal of Construction Engineering and Management, Vol. 125, No. 1, pp. 23–31, DOI: 10.1061/(ASCE)0733-9364(1999)125:1(23).

    Article  Google Scholar 

  • Tam, C. M., Tong, T. K. L., and Zhang, H. (2007). Decision making and operations research techniques for construction management, City University of Hong Kong Press, Hong Kong.

    Google Scholar 

  • Tokdemir, O. B., Arditi, D., and Balcik, C. (2006). “ALISS: Advanced linear scheduling system.” Construction Management and Economics, Vol. 24, pp. 1253–1267, DOI: 10.1080/01446190600953706.

    Article  Google Scholar 

  • Wagner, H. M., Giglio, R. J., and Glaser, R. G. (1964). “Preventive maintenance scheduling by mathematical programming.” Management Science, Vol. 10, No. 2, pp. 316–334.

    Article  Google Scholar 

  • Yen, C. (2005). Simulated annealing for optimizing linear scheduling projects with multiple resource constraints, PhD Dissertation, Purdue University.

    Google Scholar 

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Authors and Affiliations

  1. Dept. of Civil Engineering, Istanbul Technical University, Maslak, Istanbul, 34469, Turkey

    Atilla Damci

  2. Dept. of Civil, Architectural and Environmental Engineering, Illinois Institute of Technology, Chicago, Illinois, 60616, USA

    David Arditi

  3. Dept. of Civil Engineering, Istanbul Technical University, Maslak, Istanbul, 34469, Turkey

    Gul Polat

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  1. Atilla Damci
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  2. David Arditi
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  3. Gul Polat
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Correspondence to David Arditi.

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Damci, A., Arditi, D. & Polat, G. Impacts of different objective functions on resource leveling in Line-of-Balance scheduling. KSCE J Civ Eng 20, 58–67 (2016). https://doi.org/10.1007/s12205-015-0578-7

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  • DOI: https://doi.org/10.1007/s12205-015-0578-7

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