학술논문

Genetic algorithm for Generalized Resource Constrained Multi Project Scheduling Problem integrated with closed loop supply chain planning
Document Type
Conference
Source
2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) Industrial Engineering and Engineering Management (IEEM), 2016 IEEE International Conference on. :1683-1687 Dec, 2016
Subject
Aerospace
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Nuclear Engineering
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Supply chains
Genetic algorithms
Planning
Job shop scheduling
Transportation
Buildings
Capacity planning
Generalized Resource Constrained Multi Project Scheduling Problem
Supply Chain Planning
Genetic Algorithm
Mixed Integer Programming
Language
ISSN
2157-362X
Abstract
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.