Multi-objective optimization for the multi-mode finance-based project scheduling problem

Abstract

The finance-based scheduling problem (FBSP) is about scheduling project activities without exceeding a credit line financing limit. The FBSP is extended to consider different execution modes that result in the multi-mode FBSP (MMFBSP). Unfortunately, researchers have abandoned the development of exact models to solve the FBSP and its extensions. Instead, researchers have heavily relied on the use of heuristics and meta-heuristics, which do not guarantee solution optimality. No exact models are available for contractors who look for optimal solutions to the multi-objective MMFBSP. CPLEX, which is an exact solver, has witnessed a significant decrease in its computation time. Moreover, its current version, CPLEX 12.9, solves multi-objective optimization problems. This study presents a mixed-integer linear programming model for the multi-objective MMFBSP. Using CPLEX 12.9, we discuss several techniques that researchers can use to optimize a multi-objective MMFBSP. We test our model by solving several problems from the literature. We also show how to solve multi-objective optimization problems by using CPLEX 12.9 and how computation time increases as problem size increases. The small increase in computation time compared with possible cost savings make exact models a must for practitioners. Moreover, the linear programming-relaxation of the model, which takes seconds, can provide an excellent lower bound.

Keywords

multi-objective optimization / finance-based scheduling / multi-mode project scheduling / mixed-integer linear programming / CPLEX

References

[1] Abido M, Elazouni A M (2011). Multi-objective evolutionary finance based scheduling: Entire projects’ portfolio. Journal of Computing in Civil Engineering, 25(1): 85–97

[2] Abido M A, Elazouni A (2009). Improved crossover and mutation operators for genetic-algorithm project scheduling. In: IEEE Congress on Evolutionary Computation. IEEE, 1865–1872

[3] Afshar A, Fathi H (2009). Fuzzy multi-objective optimization of finance based scheduling for construction projects with uncertainties in cost. Engineering Optimization, 41(11): 1063–1080

[4] Al-Shihabi S T, AlDurgam M M (2017). A max-min ant system for the finance-based scheduling problem. Computers & Industrial Engineering, 110: 264–276

[5] Alavipour S M R, Arditi D (2018a). Impact of contractor’s optimized financing cost on project bid price. International Journal of Project Management, 36(5): 808–818

[6] Alavipour S M R, Arditi D (2018b). Optimizing financing cost in construction projects with fixed project duration. Journal of Construction Engineering and Management, 144(4): 04018012

[7] Alavipour S M R, Arditi D (2019a). Maximizing expected contractor profit using an integrated model. Engineering, Construction, and Architectural Management, 26(1): 118–138

[8] Alavipour S M R, Arditi D (2019b). Time-cost tradeoff analysis with minimized project financing cost. Automation in Construction, 98: 110–121

[9] Alghazi A, Elazouni A, Selim S (2013). Improved genetic algorithm for finance-based scheduling. Journal of Computing in Civil Engineering, 27(4): 379–394

[10] Alghazi A, Selim S Z, Elazouni A (2012). Performance of shuffled frog-leaping algorithm in finance-based scheduling. Journal of Computing in Civil Engineering, 26(3): 396–408

[11] Ali M M, Elazouni A (2009). Finance-based CPM/LOB scheduling of projects with repetitive non-serial activities. Construction Management and Economics, 27(9): 839–856

[12] Ammar M A (2011). Optimization of project time-cost trade-off problem with discounted cash flows. Journal of Construction Engineering and Management, 137(1): 65–71

[13] Burns S A, Liu L, Feng C W (1996). The LP/IP hybrid method for construction time-cost trade-off analysis. Construction Management and Economics, 14(3): 265–276

[14] Censor Y (1977). Pareto optimality in multi-objective problems. Applied Mathematics & Optimization, 4(1): 41–59

[15] Chassiakos A P, Sakellaropoulos S P (2005). Time-cost optimization of construction projects with generalized activity constraints. Journal of Construction Engineering and Management, 131(10): 1115–1124

[16] Clough R H, Sears G A, Sears S K, Segner R O, Rounds J L (2015). Construction Contracting: A Practical Guide to Company Management. Hoboken, NJ: John Wiley & Sons

[17] De P, Dunne E J, Ghosh J B, Wells C E (1995). The discrete time cost tradeoff problem revisited. European Journal of Operational Research, 81(2): 225–238

[18] De P, Dunne E J, Ghosh J B, Wells C E (1997). Complexity of the discrete time-cost tradeoff problem for project networks. Operations Research, 45(2): 302–306

[19] Doerner K F, Gutjahr W J, Hartl R F, Strauss C, Stummer C (2008). Nature-inspired metaheuristics for multi-objective activity crashing. Omega, 36(6): 1019–1037

[20] El-Abbasy M S, Elazouni A, Zayed T (2016). MOSCOPEA: Multi-objective construction scheduling optimization using elitist non-dominated sorting genetic algorithm. Automation in Construction, 71(2): 153–170

[21] El-Abbasy M S, Elazouni A, Zayed T (2017). Generic scheduling optimization model for multiple construction projects. Journal of Computing in Civil Engineering, 31(4): 04017003

[22] Elazouni A (2009). Heuristic method for multi-project finance-based scheduling. Construction Management and Economics, 27(2): 199–211

[23] Elazouni A, Abido M (2011). Multi-objective evolutionary finance-based scheduling: Individual projects within a portfolio. Automation in Construction, 20(7): 755–766

[24] Elazouni A, Abido M (2014). Enhanced trade-off of construction projects: Finance-resource-profit. Journal of Construction Engineering and Management, 140(9): 04014043

[25] Elazouni A, Alghazi A, Selim S Z (2015). Finance-based scheduling using meta-heuristics: Discrete versus continuous optimization problems. Journal of Financial Management of Property and Construction, 20(1): 85–104

[26] Elazouni A, Gab-Allah A (2004). Finance-based scheduling of construction projects using integer programming. Journal of Construction Engineering and Management, 130(1): 15–24

[27] Elazouni A, Metwally F (2005). Finance-based scheduling: Tool to maximize project profit using improved genetic algorithms. Journal of Construction Engineering and Management, 131(4): 400–412

[28] Elazouni A M, Metwally F G (2007). Expanding finance-based scheduling to devise overall-optimized project schedules. Journal of Construction Engineering and Management, 133(1): 86–90

[29] Fathi H, Afshar A (2010). GA-based multi-objective optimization of finance-based construction project scheduling. KSCE Journal of Civil Engineering, 14(5): 627–638

[30] Gajpal Y, Elazouni A (2015). Enhanced heuristic for finance-based scheduling of construction projects. Construction Management and Economics, 33(7): 531–553

[31] Glover F (1986). Future paths for integer programming and links to artificial intelligence. Computers & Operations Research, 13(5): 533–549

[32] Horowitz J (1967). Critical Path Scheduling: Management Control Through CPM and PERT. New York: Ronald Press

[33] Kerzner H, Kerzner H R (2017). Project Management: A Systems Approach to Planning, Scheduling, and Controlling. Hoboken, NJ: John Wiley & Sons

[34] Laptali E, Bouchlaghem N, Wild S (1997). Planning and estimating in practice and the use of integrated computer models. Automation in Construction, 7(1): 71–76

[35] Liu S S, Wang C J (2008). Resource-constrained construction project scheduling model for profit maximization considering cash flow. Automation in Construction, 17(8): 966–974

[36] Liu S S, Wang C J (2010). Profit optimization for multi-project scheduling problems considering cash flow. Journal of Construction Engineering and Management, 136(12): 1268–1278

[37] Moussourakis J, Haksever C (2004). Flexible model for time/cost tradeoff problem. Journal of Construction Engineering and Management, 130(3): 307–314

[38] Nkasu M, Leung K (1997). A resources scheduling decision support system for concurrent project management. International Journal of Production Research, 35(11): 3107–3132

[39] Nodet X (2019). CPLEX Optimization Studio 12.9 is available. IBM Developer

[40] Pearl J (1984). Heuristics: Intelligent Search Strategies for Computer Problem Solving. Reading, MA: Addison-Wesley Publishing

[41] Perera S (1980). Linear programming solution to network compression. Journal of the Construction Division, 106(3): 315–326

[42] Peterson S J (2009). Construction Accounting and Financial Management. Englewood, New Jersey: Pearson Prentice Hall

[43] Rudolph G (1994). Convergence analysis of canonical genetic algorithms. IEEE Transactions on Neural Networks, 5(1): 96–101

[44] Siemens N (1971). A simple CPM time-cost tradeoff algorithm. Management Science, 17(6): B-354–B-363

[45] Sonmez R, Bettemir O H (2012). A hybrid genetic algorithm for the discrete time-cost trade-off problem. Expert Systems with Applications, 39(13): 11428–11434

[46] Vanhoucke M, Debels D (2007). The discrete time/cost trade-off problem: Extensions and heuristic procedures. Journal of Scheduling, 10(4–5): 311–326

[47] Wolpert D H, Macready W G (1997). No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1): 67–82

[48] Yang I T (2007). Using elitist particle swarm optimization to facilitate bicriterion time-cost trade-off analysis. Journal of Construction Engineering and Management, 133(7): 498–505

[49] Zheng D X, Ng S T, Kumaraswamy M M (2004). Applying a genetic algorithm-based multi-objective approach for time-cost optimization. Journal of Construction Engineering and Management, 130(2): 168–176

RIGHTS & PERMISSIONS

Higher Education Press