Evolutionary computing for routing and scheduling applications

Optimization is a procedure of finding and comparing feasible solutions until no better solution can be found. Routing and scheduling are among two of the famous combinatorial optimization problems that usually engage with large-scale complicated problems. In other words, routing and scheduling algorithms need to produce feasible solutions that optimize multiple objectives concurrently as well as conform to all constraints that applied. This thesis lays the introduction together with general concepts regarding scheduling, routing optimization and evolutionary algorithms by referring to recent literatures. In depth depiction about research work includes the design of an evolutionary algorithm to solve vehicle routing problem with time windows (VRPTW) which is a case study of vehicle scheduling problem. Besides, current research that deals with optimization of a real-life vehicle routing system with truck and trailer constraints is analyzed carefully. A new problem model is proposed and optimized to provide useful information for logistics management.

Author dc:creator

• CHEW YOONG HAN

• evolutionary algorithm, computational algorithm, multiobjective optimization, vehicle routing problem, scheduling problem