Online decision making and automatic decision model adaptation

Authors:
Jörn Schönberger;Herbert Kopfer
Affiliations:
University of Bremen, Chair of Logistics, Wilhelm-Herbst-Straíe 5, 28359 Bremen, Germany;University of Bremen, Chair of Logistics, Wilhelm-Herbst-Straíe 5, 28359 Bremen, Germany
Venue:
Computers and Operations Research
Year:
2009

Citing 9
Cited 2

Algorithms for the vehicle routing and scheduling problems with time window constraints

Operations Research
Adaptive Search and the Management of Logistics Systems: Base Models for Learning Agents

Adaptive Search and the Management of Logistics Systems: Base Models for Learning Agents
Real-Time Dispatching of Guided and Unguided Automobile Service Units with Soft Time Windows

ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Scheduling the Supply Chain by Teams of Agents

HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 3 - Volume 3
On-Line Algorithms for the Dynamic Traveling Repair Problem

Journal of Scheduling
Algorithms for the on-line quota traveling salesman problem

Information Processing Letters
Reoptimization gaps versus model errors in online-dispatching of service units for ADAC

Discrete Applied Mathematics - Special issue: Traces of the Latin American conference on combinatorics, graphs and applications: a selection of papers from LACGA 2004, Santiago, Chile
Dispatching of an Electric Monorail System: Applying Metaheuristics to an Online Pickup and Delivery Problem

Transportation Science
Enhancing the point feature tracker by adaptive modelling of the feature support

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II

Decision support systems and the coordination of supply consortium partners

Computers in Industry
Impacts of imprecise demand forecasts in network capacity control: an online analysis

INOC'11 Proceedings of the 5th international conference on Network optimization

Quantified Score

Hi-index	0.01

Visualization

Abstract

The paper investigates an online version of the vehicle routing problem with time windows, in which additionally arriving requests cause the revision of so far followed routes and schedules. An extended online optimization framework is proposed, which automatically adapts to problem variations and enables the explicit consideration of up-to-date knowledge about the current performance of the controlled system. Actually, we use the mean punctuality observed in the transportation system to adjust the objective function utilized for solving the next decision problem instance. The search is guided toward least cost solutions coming along with high punctuality. We prove the applicability of this approach within comprehensive numerical experiments.