Project Scheduling Integrated with Supply Chain Management

Research Objective:

In the context of scheduling projects, this research focuses on the coordination of supply chains and project activities. First, a few meta-heuristic algorithms will be developed to complete the project within the deadline to ensure profitability. Successful project completion depends on the supply of raw materials at the right time at the right place at a minimum cost that finally ensures the project’s profitability. Thus, to ensure resource availability and timely project completion, supply chain integrated single and multi-project scheduling models will be developed for managing projects. Several hybrid meta-heuristic approaches will be developed to solve the proposed models. Our proposed algorithms will be compared with a number of state-of-the-art algorithms for validation. The managerial benefit of this study is that it helps decision making in planning, determining the best sequence when to order, how much to order, which supplier should be selected and what would be the selection criteria, how large is the inventory; are the most important factors that impacts on the project's overall profit.

The specific objectives of this research are:

• Development of algorithms for solving resource constrained project scheduling problems with discounted cash flows. 
• Development of methodologies and algorithms for simultaneous project scheduling, materials ordering procurement and supplier selection problems. 
• Development of methodologies and algorithms for supply chain integrated resource constrained multi-project scheduling problems. 
   

Research outcome:

The main possible outcomes of this research are:

• Few novel meta-heuristics approaches will be developed to solve project scheduling problems to ensure profitability.
• Novel approaches for net present value-based single and multi-project scheduling incorporating supply chain will be developed.
• Segregating the best one among a few advanced meta-heuristics approaches for solving supply chain integrated project scheduling problems. 
   

Duration:

3 years and 6 months; March 2019 to September 2022 
 

Achievements:

Journal papers:

1. Asadujjaman M, Rahman HF, Chakrabortty RK & Ryan MJ, “An Immune Genetic Algorithm for Solving NPV-based Resource Constrained Project Scheduling Problem”, IEEE Access, 9, 26177-26195, 2021. 
2. Asadujjaman M, Rahman HF, Chakrabortty RK & Ryan MJ, “Resource constrained project scheduling and material ordering problem with discounted cash flows”, Computers & Industrial Engineering, 154, 107427, 2021. 
3. Asadujjaman M, Rahman HF, Chakrabortty RK & Ryan MJ, “A Memetic Algorithm for Concurrent Project Scheduling, Materials Ordering and Suppliers Selection Problem”, Procedia Computer Science, 192, 717-726, 2021.
4. Asadujjaman M, Rahman HF, Chakrabortty RK & Ryan MJ, “Multi-operator immune genetic algorithm for project scheduling with discounted cash flows”, Expert Systems With Applications, 195, 116589, 2022.

Conference paper:

1. Asadujjaman M, Rahman HF, Chakrabortty RK & Ryan MJ, “An Immune Genetic Algorithm for Resource Constrained Project Scheduling Problem with Discounted Cash Flows”, 2020 IEEE Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, 1179-1183, 14-17 December 2020.