An intelligent zone-based delivery scheduling approach

Authors:
H. Wang;D. Xue
Affiliations:
Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada;Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada
Venue:
Computers in Industry
Year:
2002

Citing 9
Cited 4

An optimal solution method for large-scale multiple traveling salesmen problems

Operations Research
Parallel savings based heuristics for the delivery problem

Operations Research
Artificial intelligence (3rd ed.)

Artificial intelligence (3rd ed.)
Cyclic transfer algorithms for multivehicle routing and scheduling problems

Operations Research
Smalltalk: an introduction to application development using VisualWorks

Smalltalk: an introduction to application development using VisualWorks
A tabu search heuristic for the multi-depot vehicle routing problem

Computers and Operations Research
A fuzzy mathematics based optimal delivery scheduling approach

Computers in Industry
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms

Social coordination without communication in multi-agent territory exploration tasks

AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Many is more: The utility of simple reactive agents with predictive mechanisms in multiagent object collection tasks

Web Intelligence and Agent Systems
Investigating the Adaptiveness of Communication in Multi-Agent Behavior Coordination

Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Rapid identification of the optimal product configuration and its parameters based on customer-centric product modeling for one-of-a-kind production

Computers in Industry

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper introduces a zone-based delivery scheduling approach developed using artificial intelligence techniques. In this approach, delivery scheduling is conducted at three different levels: (1) classification of past delivery demand patterns and prediction of future delivery demand using a multi-level pattern clustering and matching method, (2) creation of delivery zones, including their center locations, delivery frequencies, and delivery cost rates, for each of these delivery demand patterns, and (3) identification of the optimal delivery methods, sequence, and timing parameters of delivery tasks. The system was implemented using Smalltalk, an object oriented programming language.