Abstract
Nowadays, recovery of the used products is economically more attractive than disposal, and in the recent past the growth of environmental concerns has given ‘reuse’ increasing attention. As a result, reverse logistics has a significant impact on industry. With the growing of industry in recent years, the wasted products and pollution are increasing in Taiwan. But we don’t have enough land and nature resource on this island. The treatment agencies recover the wasted products using the same vehicle to route the fixed path everyday. But they have different amount of few wasted products for recovery everyday, and this is inefficient in terms of the recovery transportation cost. In this research, we focus on the transportation stage of the wasted products recovery. Our investigation reveals that the variable cost is strongly related to the unit fuel cost, which is proportional to the carrying capacity.This study utilizes a Two-Time-Periods algorithm to minimize the total transportation cost, and it includes the clustering stage and routing stage. And then we construct the dynamic recovery VRP model to observe the transportation cost of all vehicles by satisfying service level. With the change of the demand information, the optimal vehicle routings also be changed. We generate input data randomly and analyze the result of experiment. The objective function after update of demand information is changed and it should be re-determined with new demand condition.