Research On Integrated Optimization For3-D Container Loading And VRP Of Inland Port LCL Freight

LCL freight is the owner of the goods need to be transported in a container filledinadequate, as sporadic delivery of goods, the carrier will be different from the owner of thecargo department rounded a box before shipping transportation services in the form, withsources scattered, dispersed flow characteristics. Under the traditional mode of operation, inorder to ensure the volume of containers and transport vehicles and truck utilization, carriersector classification according to the destination will be checked orders, waiting for thesame destination LCL freight transported over a box set after; to reduce storage costs, thecarrier I hope as soon as the goods will be delivered to the consignee LCL.In-land Port LCL freight and a clear distinction between the traditional, first of all,there is a clear order of their consignment delivery time requirements; Secondly, thedestination for the shipment of orders coastal ports, storage costs much higher than the dryport and cargo arriving by early dry port operators bear the storage costs. To this end, wepropose to focus on consignment orders, the same port group in Hong Kong cargo differentpurposes LCL, while minimizing the delay time to optimize its transportation policy. Onlywith the traditional LCL freight packing optimize different, In-land Port LCL freightvehicles also need to consider assignments, path optimization and transportation schedulingproblems. Therefore, the dry port LCL freight optimization problem is to integrate athree-dimensional packing optimization problem with the vehicle scheduling.To solve these problems, this paper presents a three-dimensional packing dry portsLCL freight and vehicle scheduling integrated optimization mechanisms, and theestablishment of appropriate integrated optimization model to find the optimal combinationcargo, containers, transport vehicles and transport time. While the design of themain-conducted from a hybrid genetic algorithm. Algorithm, the main stage matrix codinggenetic algorithm expressed by various combinations of cargo, containers, transportvehicles and transport time, first solution chromosome genotype chromosome transitionfrom stage heuristic algorithms for the solution of practical evaluation phenotype job, andthe different circumstances of each breach of chromosome repair treatment or punishment,and thus evaluate their fitness; primary genetic algorithm based on the individual fitness value returned from the level of genetic algorithms to continue to operate, after manyiterations to get the approximate problem the optimal solution.Finally, using MATLAB7.0programming, by comparing the experimental dataconfirmed the integrated optimization model for use in the number of containers, vehiclemileage, weight and volume of container utilization and average operating costs were betterthan traditional optimization methods produce results prove the effectiveness of integratedoptimization model and algorithm.