Title :
Study on integrated inventory-routing problems
Author :
Lou Shan-zuo ; Wu Yao-hua ; Xiao Ji-wei
Author_Institution :
Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China
Abstract :
A new method was proposed for solving the multi-depot inventory-routing problems with stochastic demands. Firstly a model was established that incorporates working inventory cost, safety stock cost and stochastic routing cost. Secondly, due to the bad convergence while utilizing traditional decomposition and coordination method (DCM) to attack the problems, the coordination values were designed by genetic algorithm (GA). Moreover, an effective tabu search (TS) was designed to cope with the expected routing costs by Monte-Carlo sampling. Finally, simulation results prove the validity of the proposed method.
Keywords :
Monte Carlo methods; distribution strategy; facility location; genetic algorithms; search problems; stock control; Monte Carlo sampling; coordination method; decomposition method; genetic algorithm; integrated inventory routing problem; multidepot inventory routing problem; safety stock cost; stochastic routing cost; tabu search; working inventory cost; Algorithm design and analysis; Convergence; Costs; Dynamic programming; Genetic algorithms; Mathematical model; Routing; Sampling methods; Stochastic processes; Vehicle safety; decomposition and coordination; genetic algorithm; inventory-routing problem; multi-depot; tabu search;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5357936