Asadujjaman, Md (2023) Planning and scheduling supply chain integrated projects. PhD thesis, University of New South Wales, Australia.
Abstract
Project planning and scheduling are two major tasks directly impacting an organization's profitability. Traditionally, project managers first schedule project activities and then plan for the associated supply chain, such as materials ordering, procurement, and supplier selection. This sequential, disintegrated approach lacks results in lower profit. Greater advantage can come from the integrated planning and scheduling of projects and their associated supply chain.This dissertation comprises three parts. The first part proposes two hybrid meta-heuristic algorithms for resource-constrained project scheduling problems with discounted cash flows (RCPSPDC). First, an immune genetic algorithm (IGA) is proposed by hybridizing genetic algorithm (GA), and immune algorithm (IA) approaches. Two local searches, named variable insertion neighborhood search (VINS) and forward-backward improvement (FBI), are also utilized in the IGA to intensify the exploration of the solutions. Second, an adaptive multi-operator-based IGA (MO-IGA) is developed that prioritizes the most-suitable operator among various GA, IA, and local search operators. Both proposed algorithms, the IGA and MO-IGA, are shown to be effective in solving benchmark RCPSPDC instances.The second part develops a mathematical model and solution approaches for supply chain integrated resource-constrained single-project scheduling problems (SCIRCSPSP). A net present value (NPV) based mixed integer programming (MIP) approach is proposed for integrated supply chain planning and scheduling activities. Three meta-heuristics, IA, GA, and IGA, are proposed to solve the supply chain integrated single-project scheduling model. The hybrid IGA maximizes project NPV better than GA and IA.The final part develops a mathematical model and solution methods for supply chain integrated resource-constrained multi-project scheduling problems (SCIRCMPSP). The proposed SCIRCMPSP not only plans for the materials ordering and suppliers selection but also for allocating local resources within a project, allotting global resources among various projects, and scheduling project activities. Five meta-heuristic approaches are designed: IA, GA, IA with FBI (IA-FBI), GA with FBI (GA-FBI), and surrogation-based GA (SGA). The proposed SGA is shown to be effective in solving the SCIRCMPSP instances and in solving multi-project scheduling benchmark instances.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Chakrabortty, Ripon Kumar; Rahman, Mohammad Humyun Fuad and Ryan, Michael J |
| Uncontrolled Keywords: | cash flows; heuristic; net present value; programming; project planning; scheduling; supplier |
| Index terms: | dissertation, profitability, net present value, supply chain planning, heuristic, project manager, project planning, exploration, programming, discounted cash flow, profit, mixed integer, cash flow, scheduling, genetic algorithm, mathematical model, project scheduling |
| Subjects: | supply chain planning, financial management, project controls, mathematical modelling, risk assessment, profession, control systems, algorithms, financial analysis, research dissemination and communication, programming, environmental resource management, operations research, economic analysis |
| Topics: | Project Management, Risk Management, Sustainability, Supply Chain Management, Business Strategy, Cost Management, Research Practice, Roles and Professions, Digital Applications, Time Control |
| Descriptive scope: | 3 PCA |
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