Genetic algorithm for Generalized Resource Constrained Multi Project Scheduling Problem integrated with closed loop supply chain planning

• Published in: 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) pp. 1683 - 1687
• Main Authors: Tayyar, S. Gholizadeh, Lamothe, J., Dupont, L.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2016
• Subjects: Buildings; Capacity planning; Generalized Resource Constrained Multi Project Scheduling Problem; Genetic Algorithm; Genetic algorithms; Job shop scheduling; Mixed Integer Programming; Planning; Supply Chain Planning; Supply chains; Transportation
• ISSN: 2157-362X
• DOI: 10.1109/IEEM.2016.7798164

This work considers a Generalized Resource Constrained Multi Project Scheduling Problem integrated with a supply chain planning model. In the model, the projects incorporate a set of activities interrelated by four types of precedence relations with positive/negative time-lags, which require two types of resources to be accomplished. The resources are considered in renewable and non-renewable types. The renewable resources come into being assigned to the activities with a limited initial availability. However, additional limited units of the resources are supposed to be rented, in order to catch up deadline of activities which hold high lateness penalty costs. The non-renewable resources of the projects are supplied by a supply chain. The model defines a production-transportation plan for supply of these resources to the projects worksites just in times. The model is solved by applying a genetic algorithm on a case from a French project called CRIBA.