Efficient scheduling method of complex batch processes with general network structure via agent-based modeling

AIChE Journal ◽  
2013 ◽  
Vol 59 (8) ◽  
pp. 2884-2906 ◽  
Author(s):  
Yunfei Chu ◽  
John M. Wassick ◽  
Fengqi You
Keyword(s):  
Network Structure ◽  
Agent Based Modeling ◽  
Batch Processes ◽  
Agent Based ◽  
General Network ◽  
Scheduling Method

Agent-Based Modeling for Carpooling

2015 ◽  
pp. 662-688
Author(s):  
Luk Knapen ◽  
Ansar-Ul-Haque Yasar ◽  
Sungjin Cho ◽  
Tom Bellemans
Keyword(s):  
Network Structure ◽  
Large Scale ◽  
Agent Based Modeling ◽  
Transportation Infrastructure ◽  
Problem Size ◽  
Agent Based ◽  
Traffic Demand ◽  
Software Structure ◽  
Large Scale Simulations ◽  
Mutually Independent

Modeling activities and travel for individuals in order to estimate traffic demand leads to large scale simulations. Most current models simulate individuals acting in a mutually independent way except for the use of the shared transportation infrastructure. As soon as cooperation between autonomous individuals is accounted for, the individuals are linked to each other in a network structure and interact with their neighbours in the network while trying to achieve their own goals. In concrete traffic-related problems, those networks can grow very large. Optimization over such networks typically leads to combinatorially explosive problems. In this chapter, the case of providing optimal advice to combine carpooling candidates is considered. First, the advisor software structure is explained; then, the characteristics for the carpooling candidates network derived for Flanders (Belgium) are calculated in order to estimate the problem size.

Agent-Based Modeling for Carpooling

2014 ◽  
pp. 232-258
Author(s):  
Luk Knapen ◽  
Ansar-Ul-Haque Yasar ◽  
Sungjin Cho ◽  
Tom Bellemans
Keyword(s):  
Network Structure ◽  
Large Scale ◽  
Agent Based Modeling ◽  
Transportation Infrastructure ◽  
Problem Size ◽  
Agent Based ◽  
Traffic Demand ◽  
Software Structure ◽  
Large Scale Simulations ◽  
Mutually Independent

Modeling activities and travel for individuals in order to estimate traffic demand leads to large scale simulations. Most current models simulate individuals acting in a mutually independent way except for the use of the shared transportation infrastructure. As soon as cooperation between autonomous individuals is accounted for, the individuals are linked to each other in a network structure and interact with their neighbours in the network while trying to achieve their own goals. In concrete traffic-related problems, those networks can grow very large. Optimization over such networks typically leads to combinatorially explosive problems. In this chapter, the case of providing optimal advice to combine carpooling candidates is considered. First, the advisor software structure is explained; then, the characteristics for the carpooling candidates network derived for Flanders (Belgium) are calculated in order to estimate the problem size.

Sign in / Sign up

Export Citation Format

Share Document