decentralized multi-project scheduling with pooling procurement possibility in construction supply network based on game theory

نوع: Type: thesis

مقطع: Segment: PHD

عنوان: Title: decentralized multi-project scheduling with pooling procurement possibility in construction supply network based on game theory

ارائه دهنده: Provider: Ali Parchami Afra

اساتید راهنما: Supervisors: Dr. Amirsaman Kheirkhah

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr. Javad Behnamian, Dr. Reza Tavakkoli-Moghaddam, Dr. Parviz Fattahi

زمان و تاریخ ارائه: Time and date of presentation: 2024

مکان ارائه: Place of presentation: Faculty of Engineering

چکیده: Abstract: Effective decision-making in multi-project planning, which includes activity scheduling, allocation of work resources (renewable resources), and procurement of materials (non-renewable resources), poses a significant challenge in maximizing organizational benefits for project managers. Improper planning can lead to resource waste, project delays, and conflicts among stakeholders, ultimately resulting in increased overall costs and a higher risk of project failure. Effective project planning necessitates the development of computational tools that encompass the influential aspects of project performance and provide support for relevant decision-making. Despite the development of mathematical models in the project scheduling literature, there are few studies that have examined the integrated aspects of project management and resource supply chain management. Another important topic is the development of collaborative relationships in a multi-project environment. Existing studies mainly focus on collaboration related to work resources planning. Despite the significance of materials management, cooperation in these resources has not received much attention. Furthermore, in the literature, it is generally assumed that project managers plan for complete coordination and openly share all information to leverage the benefits of collaboration. However, in the real world, project managers not only have their own specific goals but also prefer to selectively share information at a certain level. To address these research gaps, this study investigates two distinct problems. One is the centralized planning problem, which integrates project planning and materials supply chain management in a multi-project environment. The other is the decentralized planning problem, which enables collaboration in materials procurement for two independent projects while maintaining the independence of project managers. The centralized planning problem encompasses challenges such as multi-project investment, ordering and production planning of materials, and transportation of mobile work resources. A mixed integer programming model is developed to formulate this problem. The proposed solution method for the mathematical model is a heuristic algorithm based on Lagrangian relaxation. The decentralized planning problem involves resource investment and materials ordering with quantity discount policy for two independent projects. In this problem, two project managers have the possibility of sharing procurement of materials while maintaining decision-making independence. One project manager firstly makes decisions regarding project scheduling and materials ordering, and the other project manager plans their project considering the shared procurement benefits based on those decisions. Due to the hierarchical decision-making structure, a leader-follower Stackelberg game is used to formulate the problem, and a bi-level mixed integer programming model is presented. To solve this two-level model, two nested metaheuristic algorithms, namely nested bi-level genetic algorithm and nested bi-level particle swarm optimization, are developed. The numerical results demonstrate the desirable performance of these solution methods. The research findings showcase cost reduction in the centralized planning problem compared to the scenario where project planning and supply chain are separate. Furthermore, a cost reduction for two projects is evident in the decentralized planning scenario compared to independent planning. The outcomes of this study can offer valuable insights for both researchers and managers in the construction industry.

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