Dual objective oil and gas field development project optimization of stochastic time cost tradeoff problems

David A. Wood

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Abstract


Conducting stochastic-time-cost-tradeoff-problem (STCTP) analysis beneficially extends the scope of discrete project duration-cost analysis for oil and gas field development projects. STCTP can be particularly insightful when using a dual-objective optimization approach to locate minimum-total-project-cost solutions, and to additionally derive a Pareto frontier of non-dominated-total-project-cost solutions across a wide range of potential project durations. For STCTP project-work-item durations and costs are expressed as probability distributions and sampled with random numbers (0, 1). By controlling the fractional numbers used to sample the work-item cost distributions by formulas linked to the random numbers used to sample the work-item duration distribution, a wide range of complex time-cost relationships are readily applied. The memetic algorithm developed for constrained STCTP involves ten metaheuristics configured to focus partly on local exploitation and partly on exploration of the feasible solution space. This dual focus effectively delivers the dual objective of: 1) locating the global minimum total-project- cost solution, if it exists, or the region in the vicinity of where that solution exists; and, 2) developing a Pareto frontier. Analysis of an example project, applying eight distinct work-item time-cost relationships, demonstrates with the aid of metaheuristic profiling, that the memetic STCTP algorithm coded in Visual Basic for Applications and operated in Microsoft Excel effectively delivers on both objectives. Dynamic adjustment factors applied by some metaheuristics, derived from fat-tailed distributions adjusted by chaotic sequences, aid the efficient sampling of the feasible solution space. The metaheuristic profiles also help to fine tune the configuration of the algorithm to further enhance performance for specific work-item time-cost relationships.

Cited as: Wood, D.A. Dual objective oil and gas field development project optimization of stochastic time cost tradeoff problems. Advances in Geo-Energy Research, 2018, 2(1): 14-33, doi: 10.26804/ager.2018.01.02


Keywords


Stochastic project time-cost tradeoff problems TCTP, dual-objective nondominated sorting optimization, memetic optimization algorithm with chaotic sampling, metaheuristic profiling, pareto frontier, oil/gas project schedule-cost uncertainty model

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Afruzi, E.N., Najafi, A.A., Roghanian, E., et al. A multi-objective imperialist competitive algorithm for solving discrete time, cost and quality trade-off problems with mode-identity and resource-constrained situations. Comput. Oper. Res. 2014, 50: 80-96.

Ahari, R.M., Niaki, S.T.A. Fuzzy Optimization in cost, time and quality trade-off in software projects with quality obtained by fuzzy rule base. Int. J. Model. Optimiz. 2013, 3(2): 176-179.

Ahn, T., Erenguc, S.S. The resource constrained project scheduling problem with multiple crashable modes: A heuristic procedure. Eur. J. Oper. Res. 1998, 107(2): 250-259.

Aminbakhsh, S., Sonmez, R. Discrete particle swarm optimization method for the large-scale discrete time-cost trade-off problem. Expert Syst. Appl. 2016, 51(C): 177-185.

Ammar, M.A. Optimization of project time-cost trade-off problem with discounted cash flows. J. Constr. Eng. Manag. 2011, 137(1): 65-71.

Anagnostopoulos, K.P., Kotsikas, L. Experimental evaluation of simulated annealing algorithms for the time-cost trade-off problem. Appl. Math. Comput. 2010, 217(1): 260-270.

Azaron, A., Perkgoz, C., Sakawa, M. A genetic algorithm approach for the time/cost trade-off in PERT network. Appl. Math. Comput. 2005, 168(2): 1317-1339.

Babu, A., Suresh, N. Project management with time, cost, and quality considerations. Eur. J. Oper. Res. 1996, 88(2), 320-327.

Baker, B.M. Cost/time trade-off analysis for the critical path method: A derivation of the network flow approach. J. Oper. Res. Soc. 1997, 48(12): 1241-1244.

Berman, E.B. Resource allocation in a PERT network under continuous activity time-cost function. Manag. Sci. 1964, 10(4): 734-745.

¨O.H., Birg ¨on ¨ul, M.T. Network analysis algorithm Bettemir, for the solution of discrete time-cost trade-off problem. KSCE J. Civ. Eng. 2017, 21(4): 1047-1058.

Błaszczyk, T., Nowak, M. The time-cost trade-off analysis in construction project using computer simulation and interactive procedure. Technol. Econ. Dev. Econ. 2009, 15(4): 523-539.

Burns, S.A., Liu, L., Feng, C.W. The LP/IP hybrid method for construction time-cost tradeoff analysis. Constr. Manag. Econ. 1996, 14(3): 265-276.

Chau, D.K.H., Chan, W.T., Govindan, K. A time-cost trade-off model with resource consideration using genetic algorithm. Civ. Eng. Syst. 1997, 14(4): 291-311.

Chen, X.S., Ong, Y.S., Lim, M.H., et al. A multi-facet survey on memetic computation. IEEE Trans. Evol. Comput. 2011, 15(5): 591-607.

Cheng, M.Y., Tran, D.H. An efficient hybrid differential evolution based serial method for multimode resource-constrained project scheduling. KSCE J. Civ. Eng. 2016, 20(1): 90-100.

Cohen, I., Golany, B., Shtub, A. The stochastic time-cost tradeoff problem: A robust optimization approach. Networks 2007, 49(2): 175-188.

De, P., Dunne, E.J., Ghosh, J.B., et al. The discrete time-cost tradeoff problem revisited. Eur. J. Oper. Res. 1995, 81(2): 225-238.

Deckro, R.F., Herbert, J.E., Verdini, W.A., et al. Nonlinear time/cost tradeoff models in project management. Comput. Ind. Eng. 1995, 28(2): 219-229.

Demeulemeester, E.L., Herroelen, W.S., Elmaghraby, S.H. Optimal procedures for the discrete time-cost trade-off problem in project networks. Eur. J. Oper. Res. 1996, 8(1): 50-68.

Elazouni, A. Heuristic method for multi-project finance-based scheduling. Constr. Manag. Econ. 2009, 27(2): 199-211.

Elbeltagi, E., Hegazy, T., Grierson, D. Comparison among five evolutionary-based optimization algorithms. Adv. Eng. Inf. 2005, 19(1): 43-53.

Elbeltagi, E., Hegazy, T., Grierson, D. A modified shuffled frog-leaping optimization algorithm: Applications to project management. Struct. Infrastruct. Eng. 2007, 3(1): 53-60.

Elmaghraby, S.E. Resource allocation via dynamic program-ming in activity Networks. Eur. J. Oper. Res. 1993, 64(2): 199-215.

El-Rayes, K., Kandil, A. Time-cost-quality trade-off analysis for highway construction. J. Constr. Eng. Manag. 2005, 131(4): 477-486.

Eusuff, M., Lansey, K., Pasha, F. Shuffled frog leaping algo-rithm: A memetic metaheuristic for discrete optimization. Eng. Optimiz. 2006, 38(2): 129-154.

Falk, J.E., Horowitz, J.L. Critical path problem with concave cost curves. Manag. Sci. 1972, 19(4): 446-455.

Feng, C.W., Liu, L., Burns, S.A. Using genetic algorithms to solve construction time-cost trade-off problems. J. Comput. Civ. Eng. 1997, 11(3): 184-189.

Fondahl, J.W. A non-computer approach to the critical path method for the construction industry. Palo Alto, Stanford University, 1962.

Fulkerson, D.R. A network flow computation for project cost curves. Manag. Sci. 1961, 7(2): 167-178.

Garg, P. A comparison between memetic algorithm and genetic algorithm for the cryptanalysis of simplified data encryption standard algorithm. Int. J. Netw. Secur. Appl. 2009, 1(1): 34-42.

Geem, Z.W. Multi-objective optimization of time-cost trade-off using harmony search. J. Constr. Eng. Manag. 2010, 136(6): 711-716.

Ghoddousi, P., Eshtehardian, E., Jooybanpour, S., et al. Multi-mode resource-constrained discrete time-cost-resource optimization in project scheduling using non-dominated sorting genetic algorithm. Autom. Constr. 2013, 30: 216-227.

Gomes, H.C., Neves, F.D.A.D., Souza, M.J.F. Multi-objective metaheuristic algorithms for the resource-constrained project scheduling problem with precedence relations. Comput. Oper. Res. 2014: 44: 92-104.

Gutjahr, W.J., Strauss, C., Wagner, E. A stochastic Branch-and-Bound approach to activity crashing in project management. Informs J. Comput. 2000, 12(2): 125-135.

Hagstrom, J.N. Computational complexity of PERT problems. Networks 1988, 18(2): 139-147.

Harvey, R.T., Patterson, J.H. An implicit enumeration algorithm for the time/cost tradeoff problem in project network analysis. Manag. Sci. 1979, 4(3): 107-117.

Hegazy, T. Optimization of construction time-cost trade-off analysis: Using genetic algorithms. Can. J. Civ. Eng. 1999, 26(6): 685-697.

Hindelang, T.J., Muth, J.F. A dynamic programming algorithm for decision CPM networks. Oper. Res. 1979, 27(2): 225-241.

Huang, L., Ding, S., Yu, S., et al. Chaos-enhanced Cuckoo search optimization algorithms for global optimization. Appl. Math. Model. 2016, 40(5): 3860-3875.

Iranmanesh, H., Skandari, M.R., Allahverdiloo, M. Finding Pareto optimal front for the multi-mode time, cost quality trade-off in project scheduling. Int. J. Econ. Manag. Eng. 2008, 2(4): 397-401.

Ke, H. A genetic algorithm-based optimizing approach for project time-cost trade-off with uncertain measure. J. Uncertainty Anal. Appl. 2014, 2(1): 8.

Ke, H., Liu, B. Project scheduling problem with stochastic activity duration times. Appl. Math. Comput. 2005, 168(1): 342-353.

Ke, H., Ma, W., Ni, Y. Optimization models and a GA-based algorithm for stochastic time-cost trade-off problem. Appl. Math. Comput. 2009, 215(1): 308-313.

Kelley, J.E. Critical path planning and scheduling: Mathemat-ical basis. Oper Res. 1961, 9(3): 296-320.

Khang, D.B., Myint, Y.M. Time, cost and quality trade-off in project management: A case study. Int. J. Proj. Manag. 1999, 17(4): 249-256.

Kim, J.Y., Kang, C.W., Hwang, I.K. A practical approach to project scheduling: Considering the potential quality loss cost in the time-cost tradeoff problem. Int. J. Proj. Manag. 2012, 30(2): 264-272.

Koo, C., Hong, T., Kim. S. An integrated multi-objective optimization model for solving the construction time-cost trade-off problem. J. Civ. Eng. Manag. 2015, 21(3): 323-333.

Lamberson, L.R., Hocking, R.R. Optimum time compression in project scheduling. Manag. Sci. 1970, 16(10): 597-606.

Li, B., Jiang, W.S. Optimizing complex functions by chaos search. Cybern. Syst. 1998, 29(4): 409-419.

Li, H., Love, P. Using improved genetic algorithms to facilitate time-cost optimization. J. Constr. Eng. Manag. 1997, 123(3): 233-237.

Lin, J.H., Chou, C.W., Yang, C.H., et al. A chaotic levy flight bat algorithm for parameter estimation in nonlinear dynamic biological systems. J. Comput. Inf. Technol. 2012, 2(2): 56-63.

Monghasemi, S., Nikoo, M.R., Fasaee, M.A.K., et al. A novel multi criteria decision making model for optimizing time-cost-quality trade-off problems in construction projects. Expert Syst. Appl. 2015, 42(6): 3089-3104.

Moscato, P. On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms. Caltech Concurrent Computation Program 1989, 826: 1-67.

Moselhi, O. Schedule compression using the direct stiffness method. Can. J. Civ. Eng. 1993, 20(1): 65-72.

Moselhi, O., Deb, B. Project selection considering risk. Constr. Manag. Econ. 1993, 11(1): 45-52.

Mungle, S., Benyoucef, L., Son, Y.J., et al. A fuzzy clustering-based genetic algorithm approach for time-cost-quality trade-off problems: A case study of highway construction project. Eng. Appl. Artif. Intell. 2013, 26(8): 1953-1966.

Ng, S.T., Zhang, Y. Optimizing construction time and cost using ant colony optimization approach. J. Constr. Eng. Manag. 2008, 134(9): 721-728.

Pollack-Johnson, B., Liberatore, M.J. Incorporating quality considerations into project time/cost tradeoff analysis and decision making. IEEE Trans. Eng. Manag. 2006, 53(4): 534-542.

Pour, N.S., Modarres, M., Tavakkoli-Moghaddam, R. Time-Cost-Quality trade-off in project scheduling with linguis-tic variables. World Appl. Sci. J. 2012, 18(3): 404-413.

Rahimi, M., Iranmanesh, H. Multi-objective particle swarm optimization for a discrete time, cost and quality trade-off problem. World Appl. Sci. J. 2008, 4(2): 270-276.

Rashtchi, V, Hatami, M, Sabouri, M. Chaotic shuffled frog leaping optimization algorithm. Proc. Int. Conf. Adv. Comput. Eng. 2012, 13-16.

Rasmy, M.H., Abdelsalam, H.M.E., Hussein, R.R. Multi-objective time-cost trade-off analysis in critical chain project networks using Pareto simulated annealing. Proceeding Presented at the sixth international conference on informatics and systems(INFOS2008), Cairo, Egypt, March, 2008.

Reda, R., Carr, R.I. Time-cost trade-off among related activities. J. Constr. Eng. Manag. 1989, 115(3): 475-486.

Robinson, D.R. A dynamic programming solution to cost-time tradeoff for CPM. Manag. Sci. 1975, 22(2): 158-166.

Rostami, M., Moradinezhad, D., Soufipour, A. Improved and competitive algorithms for large scale multiple resource constrained project-scheduling problems. KSCE. J. Civ. Eng. 2014, 18(5): 1261-1269.

Saif, A.G.F., Abbas, S., Fayed, Z. Applying IWD algorithm for discrete time, cost and quality trade-off in software projects with expressing quality by defects. J. Emerging Trends Comput. Inf. Sci. 2015, 6(2): 119-124.

Siemens, N. A simple CPM time-cost tradeoff algorithm. Manag. Sci. 1971, 17(6): 354-363.

Singh, G., Ernst, A.T. Resource constraint scheduling with a fractional shared resource. Oper. Res. Lett. 2011, 39(5): 363-368.

Sonmez, R., Bettemir, ¨O.H. A hybrid genetic algorithm for the discrete time-cost trade-off problem. Expert Syst. Appl. 2012, 39(13): 11428-11434.

Suh, W.J., Park, C.S., Kim, D.W. Heuristic vs. meta-heuristic optimization for energy performance of a post office building. Paper Presented at 12th Conference of Inter-national Building Performance Simulation Association, Sydney, Australia, 14-16 November, 2011.

Tareghian, H.R., Taheri, S.H. On discrete time cost quality trade off problem. Appl. Math. Comput. 2006, 181(2): 1305-1312.

Tavana, M., Abtahi, A.R., Khalili-Damghani, K. A new multi-objective multi-mode model for solving preemptive time-cost-quality trade-off project scheduling problems. Expert Syst. Appl. 2014, 41(4): 1830-1846.

Vahidi, R. Do tradeoff models have what it takes to make a real tradeoff? Procedia Soc. Behav. Sci. 2013, 74: 71-80.

Vanhoucke, M., Debels, D. The discrete time/cost trade-off problem: Extensions and heuristic procedures. J. Scheduling 2007, 10(4): 311-326.

Van Peteghem, V., Vanhoucke, M. A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem. Eur. J. Oper. Res. 2010, 201(2): 409-418.

Wang, L., Zheng, D.Z., Lin, Q.S. Survey on chaotic optimization methods. Comput. Technol. Autom. 2001, 20(1): 1-5.

Wollmer, R.D. Critical path planning under uncertainty. Math. Program. Study 1985, 25: 164-171.

Wood, D.A. Metaheuristic profiling to assess performance of hybrid evolutionary optimization algorithms applied to complex wellbore trajectories. J. Nat. Gas Sci. Eng. 2016a, 33: 751-768.

Wood, D.A. Hybrid cuckoo search optimization algorithms applied to complex wellbore trajectories aided by dynamic, chaos-enhanced, fat-tailed distribution sampling and metaheuristic profiling. J. Nat. Gas Sci. Eng. 2016b, 34: 236-252.

Wood, D.A. Evolutionary memetic algorithms supported by metaheuristic profiling effectively applied to the optimization of discrete routing problems. J. Nat. Gas Sci. Eng. 2016c, 35: 997-1014.

Wood, D.A. Gas and oil project time-cost-quality tradeoff: in-tegrated stochastic and fuzzy multi-objective optimization applying a memetic, nondominated, sorting algorithm. J. Nat. Gas Sci. Eng. 2017, 45: 143-164.

Wuliang, P., Chengen, W. A multi-mode resource-constrained discrete time-cost tradeoff problem and its genetic algorithm based solution. Int. J. Proj. Manag. 2009, 27(6): 600-609.

Yang, X.S., Deb, S. Cuckoo search via L ´evy flights. Paper Presented at World Congress on Nature & Biologically Inspired Computing, Coimbatore, India, 9-11 December, 2009.

Zahraie, B., Tavakolan, M. Stochastic time-cost-resource utilization optimization using nondominated sorting genetic algorithm and discrete fuzzy sets. J. Constr. Eng. Manag. 2009, 135(11): 1162-1171.

Zareei, M., Hassan-Pour, H.A., Mosadegh-Khah, M. Time-cost tradeoff for optimizing contractor NPV by cost payment and resource constraints using NSGA-II algorithm (case study: Bandar abbas gas condensate refinery project). J. Math. Comput. Sci. 2014, 12: 12-26.

Zhang, H., Xing, F. Fuzzy-multi-objective particle swarm op-timization for time-cost-quality tradeoff in construction. Autom. Constr. 2010, 19(8): 1067-1075.

Zhang, L.H., Zou, X., Qi, J.X. A trade-off between time and cost in scheduling repetitive construction projects. J. Ind. Manag. Optimiz. 2015, 11(4): 1423-1434.

Zheng, D.X.M., Ng, S.T. Stochastic time-cost optimization model incorporating fuzzy sets theory and nonreplaceable front. J. Constr. Eng. Manag. 2005, 131(2): 176-186.

Zheng, D.X.M., Ng, S.T., Kumaraswamy, M.M. Applying a genetic algorithm-based multi-objective approach for time-cost optimization. J. Constr. Eng. Manag. 2004, 130(2), 168-176.

Zheng, D.X.M., Ng, S.T., Kumaraswamy, M. Applying Pareto ranking and niche formation to genetic algorithm-based multi objective time-cost optimization. J. Constr. Eng. Manag. 2005, 131(1): 81-91.

Zheng, H. Multi-mode discrete time-cost-environment trade off problem of construction systems for large-scale hydroelectric projects. Paper Presented at the Ninth International Conference on Management Science and Engineering management, Karlsruhe, Germany, 21-23 July, 2015.

Zhou, J., Love, P.E.D., Wang, X., et al. A review of methods and algorithms for optimizing construction scheduling. J. Oper. Res. Soc. 2013, 64(8): 1091-1105.


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