Abstract
Multiple projects are often managed and run in a decentralized setting. In this paper, considering the uncertainty in project implementation, we study the distributed multi-project scheduling problem with uncertain duration. A multi-PR heuristic (MPR-H) is then proposed to dynamically coordinate the global resource conflicts while minimizing the expected total tardiness cost. Three priority rules based on current known information are also proposed and incorporated in our approach. We further consider the opportunistic behaviour of self-interested agents and design a payment negotiation process which is added to the MPR-H. In this paper, we then evaluate the performance of the MPR-H on the benchmark dataset MPSPLIB. The computational results confirm that MPR-H achieves significant improvements in comparison with several state-of-the-art distributed/centralized algorithms. The proposed algorithm also provides the senior manager with an efficient method to allocate global resources for large-size and strong conflicting instances under various activity duration distributions. Besides, we show that multi-projects with relative slack global resource constraints are more affected by the change of uncertainty. By analyzing the strategic behaviour of the agents in problems with two projects, we also show that in our MPR-H with payment negotiation approach, rational agents have to behave truthfully that is the dominant-strategy equilibrium leading to high-quality results.
Highlights
Business firms often manage multiple projects simultaneously to improve their return of investment [1]
This paper is devoted to solving the distributed multi-project scheduling problem under uncertain durations, where the activity durations are subject to a known probability distribution
A comprehensive computational experiment on the MPSPLIB benchmark is performed to examine the performance of our proposed algorithm and analyze the agents’ strategic behaviour
Summary
Business firms often manage multiple projects simultaneously to improve their return of investment [1]. With the rapid development of the Internet technology and globalization, the multi-project environment is becoming more distributed, where projects might be located at various places and each project is managed by an individual decisionmaker (i.e., a project manager) [6] In such cases, the project managers independently schedule all activities within the respective projects. The global resources are often limited and even scarce This becomes a distributed resource-constrained multi-project scheduling problem (DRCMPSP) [7]. In DRCMPSP, the projects share limited global resources and each project is scheduled by an individual project manager. We propose a multi-PR (priority rule) based heuristic (MPR-H) approach which dynamically determines the global resource allocation at each decision point. The results confirm that the proposed approach provides the senior manager with an efficient method to allocate the global resources even for large-size and strong conflicting instances with various distributions of the activity duration.
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