Applied Mechanics and Materials Vols. 744-746

Abstract: To reduce logistics costs and enhance operation efficiency, selecting a suitable logistics center location has become a very important issue for manufacturing, sales and logistics industries. The selection of logistics centers is a most important decision owing to the need to consider various criteria that involve a complex decision process in which multiple requirements and uncertain conditions have to be taken into consideration simultaneously. In this paper, we propose a multiple criteria decision-making (MCDM) model based on fuzzy-set theory. And it is applied to the evaluation and selection of logistic centers. In the model, quantitative and qualitative criteria as well as the different importance weights of all the criteria are considered. A FMCG logistics center location example is used to elaborate how to use this model; meanwhile, the method is proved more scientific and reliable.

Abstract: The logistics distribution modes have always been the bottleneck factors that restrict the development of fresh agricultural products’ e-commerce. Based on the studying of traditional logistics distribution modes, this paper points out five problems of how to create the e-commerce logistics distribution system. This thesis analyses the e-commerce logistics distribution modes of fresh agricultural products and the business process; summarizes the advantages and problems of the e-commerce logistics distribution of fresh agricultural products; finally, puts forward reasonable suggestions for fresh agricultural products e-commerce logistics distribution mode.

Abstract: The article researches on the development model of the National Public Information Sharing Platform for Transportation& Logistics (LOGINK), in which the author introduces the function orientation of the LOGINK. Based on the current development status of the platform, the article predicts the development trend in the future. Then, it analyzed the necessary of the transformation of the LOGINK’s development model. In order to ensure the sustainable development of the platform, this paper proposes that the development model should be changed from “Charity” to “Charity + Appreciation”. Lastly, the article gives a plan about the service model and profit model of the platform in the future.

Abstract: In an increasingly competitive global market environment, supply chain competition has become the key content of industry competition in the new period. At present, the real competition is not the competition between enterprises and enterprises, but competition between supply chain and supply chain. While the key of the supply chain competition is the competition of logistics network, an efficient and suitable for logistics network can not only help enterprises to seize market share, but also can greatly reduce logistics costs to improve enterprise core competitiveness. To solve the problems existing in the supply chain network expansion, I use genetic algorithms to make model optimization.

Abstract: This paper designs a model of muti-echelon closed-loop supply chain network (CLSC network). CLSC network includes raw material suppliers, manufacturers, distribution centers, collection centers and customer zones. The purpose of this paper is to minimize the overall costs of CLSC network. The overall costs include transportation cost, fixed cost, variable cost, penalty cost. This model is a mixed integer linear programming model. In general, it is very difficult to solve the model. Cplex12.6 is used in order to deal with this model. The results show that this model can be solved by Cplex12.6 well.

Abstract: This papers focus on the transportation optimal model and algorithm in the multimodal transportation. According to the network characteristic of multimodal transportation system, the transportation modes combinatorial optimization model is designed. Considering the complexity of multimodal transportation, Genetic Algorithm (GA) is used as the efficient tool to solve the optimization problem. At last we use an example to verify the feasibility of the model.

Abstract: In this paper, we try to solve 3D offline packing optimization problem by combining two methods-genetic algorithm’ global performance and simulated annealing algorithm’ local performance. Given Heuristic rules in loading conditions, we use the optimal preservation strategy and the roulette wheel method to choose selection operator, integrating simulated annealing algorithm into genetic algorithm , and achieving code programming and algorithms by Matlab.This paper carries out an actual loading in a vehicle company in Changchun City, then makes a contrast between the final optimization results and each suppliers’ current packing data.The experimental results show that the algorithm has a certain validity and practicability in multiple container packing problem.

Abstract: Based on enterprises’ risk sharing strategy, transportation decisions such as the mode of transportation, transport volume and frequency are analyzed in this paper with a single supplier and multiple retailers as a whole research object. The effect of transportation decision on transportation cost is quantified, and a logistics cost model is established based on the comprehensive consideration of transportation cost and inventory cost. The logistics cost under risk sharing mode is calculated by using a numerical example of different kinds of products and is compared with the logistics cost under traditional mode, which provides a basis for effective logistics cost control.

Abstract: For aim applied to develop Intelligent Transportation System (ITS), a traffic incident detection method based on Reduced Error Pruning Tree (REPTree) algorithm of decision tree is presented. Different from unpruned decision tree, REPTree model is a fast decision tree learner which builds a decision tree using information gain as the splitting criterion, and prunes it using reduced-error pruning. The detection performance of the REPTree was compared to multi-layer feed forward neural networks (MLFNN) and Radical Basis Function neural networks (RBFNN) which yield superior incident detection performance in the previous studies. The experimental results indicate that REPTree model is competitive with MLFNN and RBFNN.

Abstract: As the siginificant factors influence passengers comfort, the vehicle celebration performance may easy to cause accidents, such as hard acceleration and deceleration performance. In order to find the relationship between passengers comfort and celebration performance, 35 passengers and three professional drivers were recruited in the field experiment. The passengers’ comfort feelings were analysed by subject questionnaires, the acceleration and deceleration data were received by CAN bus.The Artificial Neural Networks (ANNs) model was elaborated to estimate and predict the passengers comfort level of driver unsafe acceleration behavior situations. Therefore, the subject views of the passengers could be compared to object acceleration data. An ANN is applied to interconnect output data (subjective rating) with input data (objective parameters). Finally, it is found the investigatioin have demonstrated that the objective values are efficiently correlated with the subjective sensation. Thus, the presented approach can be effectively applied to support the drive train development of bus.