Researches and Publications

1) Tavakolan Mehdi, Chokan Farzad, Dadashi Mostafa, “Project portfolio selection and scheduling with multi-mode resource constraints ”, submitted

Abstract:
Optimum portfolio selection is one of the critical topics in project management, which has captured researchers’ attention for more than 60 years. Scheduling selected projects to maximize profit and making execution of project portfolio feasible are important issues in this topic. In this research, a comprehensive model is presented to conduct simultaneous project selection and scheduling while maximizing project portfolio’s net present value and minimizing its resource fluctuations. Constrains such as project’s upper bound duration, project portfolio’s needed surety, required cash in hand, and required resources are also satisfied to form feasible solutions from contractor’s point of view. Finally, project portfolio with its schedule, resource usage, cash flow, and profit are outputted. Project portfolio analysis sub model is developed to analyze selected projects. Consequently, optimization and selection sub models are developed by Continuous Ant Colony Optimization algorithm to form, schedule and optimize project portfolios. The optimization results demonstrates that the presented model allows contractors to form an optimal project portfolio while considering financial and resource constraints. In addition, an improvement in scheduling of the selected projects is observed.

The results of the developed model is also added to this page that can be used by future researches as comparison base. In this research, 6 projects were used. The task number for project 1, 2, 3, 4, 5 and 6 is 10, 12, 14, 16, 18 and 20 respectively. The input project related parameters are:

Category

Item

Project #1 (j10)

Project #2 (j12)

Project #3 (j14)

Project #4 (j16)

Project #5 (j18)

Project #6 (j20)

Contractual terms

Start day

0

14

32

32

27

50

Day segment

1

1

1

1

1

1

Contract duration

25

29

28

41

52

35

Guarantee period duration

10

15

20

50

16

20

Contractor profit rate

15%

15%

15%

15%

15%

15%

Surety percent

5%

5%

5%

5%

5%

5%

Good faith gesture percent

10%

10%

10%

10%

10%

10%

 

Maximum duration factor

1.25

1.25

1.25

1.25

1.25

1.25

Financial terms

Earnings delay

5

10

7

7

10

7

Total cost

281

266

355

361

383

468

NPV

40.79

38.03

50.77

51.17

54.29

66.51

Required cash in hand

76.67

119.5

121.38

103.56

143.71

125.2

Resource peak 1(R1)

19

18

20

17

14

17

Resource peak 2(R2)

9

14

11

12

13

19

Number of tasks

12

14

16

18

20

22

 

Penalty

0.8

0.7

0.9

0.5

0.4

0.7

 

Bonus

0.5

0.45

0.35

0.3

0.3

0.5

The input contractor related parameters are listed below:

Item

Value

Available
cash in hand

150

Available
surety

100

Available
resource R1

25

Available
resource R2

25

Importance
factor of resource R1

1

Importance
factor of resource R2

1

Relative Importance of NPV to Resource

0.7

The before and after optimization results can be downloaded from here.
Link: [Download not found]

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1) Abbasianjahromi Hamidreza, Rajaie Hossein, Shakeri Eghbal, Chokan Farzad, (2014), “A New Decision Making Model for Subcontractor Selection and its Order Allocation”, Project Management Journal, Vol. 45, No.1, 55-66

Abstract:
All experts agree on the importance of subcontracting. The high impact of subcontractors on the construction process means that the selection of subcontractors is a sensitive activity. Previous investigations documented the selection of subcontractors based on criteria but did not consider the number of subcontracted tasks. This paper explores allocating the best portion of tasks to subcontractors while optimizing the risk and cost in the fixed project schedule. The study’s main finding demonstrates that subcontractor selection without attention to the order allocation is not a realistic approach; therefore, a hybrid model that applies continuous ant colony and fuzzy set theory is proposed.