DocumentCode :
3746207
Title :
Location-aware workflow scheduling in supply chains based on multi-agent systems
Author :
Fu-Shiung Hsieh
Author_Institution :
Dept. of Computer Science and Information Engineering, Chaoyang University of Technology, Taiwan
fYear :
2015
Firstpage :
441
Lastpage :
448
Abstract :
In construction industry, companies form a supply chain to respond to business opportunities. The complex workflows, dependency between partners and their location pose a big challenge in construction project management. How to schedule activities to meet the construction project requirements under resource constraints is an important issue. To create a feasible schedule for a construction project, companies in a typical construction supply chain need to negotiate with each other. Development of an effective software system to support negotiation and collaboration between the partners in a construction supply chain is urgent. Execution of workflows in a construction project usually depends on location. Although workflow management problems have been extensively studied for decades, location information of workflows is rarely taken into account in existing literature. In this paper, we will study the development of a location-aware workflow scheduling system for construction supply chains. We will propose a flexible scheduling system to optimize the construction project schedule based on collaboration of entities/partners in a construction supply chain. We propose a methodology that includes modeling of location-aware workflows in construction projects based on formal workflow models and develop a technique to transform workflow models to formulate and solve a project scheduling problem. We propose architecture to implement a location-aware multi-agent scheduling system based on JADE and Google API. The proposed methodology is verified by an example.
Keywords :
"Computational modeling","Distributed computing","Computer architecture","Optimization"
Publisher :
ieee
Conference_Titel :
Technologies and Applications of Artificial Intelligence (TAAI), 2015 Conference on
Electronic_ISBN :
2376-6824
Type :
conf
DOI :
10.1109/TAAI.2015.7407087
Filename :
7407087
Link To Document :
بازگشت