A Ship-Construction Dataset for Resource Leveling Optimization in Large Project Management Problems

Published: 1 June 2023| Version 2 | DOI: 10.17632/v8y9gp3kpn.2
Contributors:
Christos Kyriklidis,

Description

The present dataset concerns the basic elements of a real-world ship construction project. The following information is provided: 1) duration of activities, 2) correlations of activities, and resources of activities. The duration of activities and the correlation of activities are required for the construction of the project network. The project network is based on the well-known Critical Path Method and provides the limits for the start times of the activities. These limits range between the Early Start (ES) and Late Start (LS) time of every activity and sort the activities into two groups: 1) critical activities (ES=LS) and 2) non-critical activities (ES≠LS). When the project network is formed, the resource profile of the project can be developed. A resource profile is produced from the resource requirements per day of every executed activity. The project network and the resource profile of the project are the necessary information needed for defining and handling the resource leveling optimization problem. Resource leveling is a highly complex optimization problem corresponding to adjusting a project’s timeline (start and end dates) with the aim of matching resource allocation demands. The problem is particularly complex when a project is large and involves hundreds or even thousands of activities. Its successful solution is equivalent to considerable profits for the involved construction groups through the efficient management of their resources. The specific dataset has never been published before elsewhere and now there is a clear opportunity to provide these data for testing and benchmark experimentation to interested researchers.

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Institutions

University of the Aegean Department of Financial and Management Engineering

Categories

Business, Operations Research, Project Management, Resource Allocation, Decision Making Management

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