Abstract
Recently consumer needs become more and more various and they require fiexible transportation systems in physical distribution as well as flexible manufacturing systems in production.
In this paper, we propose an efficient method for road transportation scheduling, which combines a knowledge base system with optimization algorithms.
We consider the problem to make a schedule for road transportation between cities. This is a large scale combinatorial problem and constraints are not fixed but flexibly changed.
The basic approaches to this problem are considered to be as follows.
1) Mathematical programming approach
2) Knowledge engineering approach
It is not guaranteed that a mathematical programming method can be applied when constraints are changed. In knowledge engineering approach, it is difficult to acquire useful knowledges. Considering these things, we construct a scheduling method which combines knowledge bases and optimization algorithms. Knowledge bases describe the constraints and produce candidates of solution by checking the feasibility of them. The solution space generated by the knowledge bases is efficiently searched by optimization algorithms. The proposed method makes it possible to get near optimal solutions for large scale problems in short time.
The schedule can be easily modified by a planner in the process of generating solution candidates. When constraints are changed, this method can be applied only by modifying the knowledge bases.
