Title :
A genetic algorithm for vehicle routing problems with stochastic demand and soft time windows
Author :
Mak, K.L. ; Guo, Z.G.
Author_Institution :
Dept. of Ind. & Manuf. Syst. Eng., Hong Kong Univ., Hong Kong
Abstract :
We study the stochastic vehicle routing problem with soft time windows (SVRPSTW). Vehicles with limited capacity are routed from the central depot to a set of geographically dispersed customers with unknown demands, predefined presence probability and time windows. The late arrival at the customer is allowed by adding a penalty to the objective value. A mathematical model is developed to describe the behavior of this kind of delivery system. A novel age based genetic scheduling algorithm is proposed as an optimization tool to solve this intractable vehicle routing problem in order to minimize the total cost. The effectiveness of the proposed scheduling algorithm is illustrated by using a set of randomly generated numerical examples. The results indicate that the proposed genetic approach is a simple but effective means for solving these problems
Keywords :
genetic algorithms; minimisation; probability; scheduling; stochastic processes; transportation; vehicles; genetic scheduling algorithm; geographically dispersed customers; intractable vehicle routing problem; late arrival; mathematical model; optimization tool; predefined presence probability; soft time windows; stochastic demand; stochastic vehicle routing problems; total cost minimization; Capacity planning; Costs; Genetic algorithms; Logistics; Mathematical model; Routing; Scheduling algorithm; Stochastic processes; Time factors; Vehicles;
Conference_Titel :
Systems and Information Engineering Design Symposium, 2004. Proceedings of the 2004 IEEE
Conference_Location :
Charlottesville, VA
Print_ISBN :
0-9744559-2-X
DOI :
10.1109/SIEDS.2004.239880
