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JMI is an advanced inventory management method, how to implement JMI to reduce overall supply chain inventory cost and how to undertake profit allocation is a hot topic in the study of inventory management. But the current study rarely considering BOM, much less BOM's impact on supply chain inventory cost under the multi-product environment. This paper studies the two level supply chain including single manufacturer and multi-supplier of multi-product, and analyzes the BOM of multi-product, then propose a multi-product JMI model based on BOM and use a numerical example to demonstrate its validity.

Using Kano model to analyze the service quality of B2C e-commerce sites, this paper aims to explore the classification of service quality attributes and further to analyze the influence of each service quality attributes on customer satisfaction. Research results show that the service quality attributes of current B2C e-commerce sites can be divided into three categories, which are must-be quality, one-dimension quality and indifferent quality; the results also analyzes the degrees to which each service quality attribute affects customer satisfaction to provide a reference for B2C e-commerce sites to improve their service quality.

Regional low-carbon innovation system is the effective regional response mechanism to deal with energy and environmental threats. Regional low-carbon innovation system strategic frame construction includes four interrelated key component: innovation subject, innovation resources, innovative environment and operation mechanism. This paper discuss the present situation and the bottleneck on developing low-carbon economy of Changsha-Zhuzhou-Xiangtan (CZT) urban agglomeration, on this basis, building the frame model of regional low-carbon innovation system and analyzing the coordination mechanism of component. Finally puts forward the overall development ideas and suggestions of CZT regional low-carbon innovation system.

To meet the development trend of the multi-project operations, this paper describes the concepts of project family and general work breakdown structure (GWBS), and then presents a data mining approach to forming GWBS. Work breakdown structure (WBS) instances are represented by a tree graph, and then we propose a similarity metric between a pair of WBS trees. The results of the pairwise comparisons are used as a distance metric for the following k-medoids clustering algorithm that groups the project WBSs into project families. Each classified cluster represents a project family, and it is expressed by a GWBS. Since the GWBS comes from large amount of historical WBS data, its adaptability and configuration ability are improved effectively, and all of these provide a strong guarantee for enterprises to respond quickly to customer needs.

Arc consistency has been successfully applied to binary constraint satisfaction problem but cannot be generalized to effectively preprocess non-binary constraint satisfaction problem (NCSP). Associated constraint based non-binary arc consistency (nACBA) for preprocessing NCSP was proposed in this paper. Some NCSP instances generated by random NCSP generator were first preprocessed by nACBA and non-binary arc- consistency (nAC) respectively, and then solved by backtracking algorithm. Performances of backtracking, nACBA based backtracking and nAC based backtracking were evaluated and compared. The experimental results indicate that nACBA based backtracking is even more robust than the other two algorithms, which means associated constraint based non-binary arc-consistency can more effectively eliminate inconsistent values from the domains of variables or redundant constraint tuples from constraints than non-binary arc consistency.

These based on the analysis of features of mould production in MC enterprise including one shot, single piece, random arrival of order and technology diversity, the paper proposed to schedule mould production plan by using scheduling method in project management field, so that MC enterprise can achieve production target with the lowest cost in limited time. Meanwhile, based on the analysis of classic multi-mode project scheduling problem model, the paper constructed mould production scheduling model in MC enterprise and solved it though ant colony algorithm. Finally, the paper realized the solution progress by programming the algorithm in language C++ and experiments were done through instances in LIBPSP. Above 70% instances can obtained optimal results. Average deviation of various instances ranges from 5% to 9%. The result indicates that parameters selection of ant colony algorithm effects performance greatly, besides, optimal parameters various with the activity number.

MMRCPSP/MIN has been proved to be a NP-hard problem. Based on the introduction of model of project scheduling problem with minimum time lag developed by Roland Heilmann, the paper analyzed two swarm intelligence algorithms which have good performance in solving combinatorial optimization problem-ACO and PSO algorithms. Based on analysis of these algorithms' defects, the paper proposed that the defects of ACO algorithm such as hard to converge, performance significantly affected by parameters, high requirement for parameters and so on, can be made up by the high convergence of PSO algorithm. The parameters of ACO algorithm were set in terms of the solution of PSO algorithm. Through particle swarm iteration and making convergence effect and better objective solution of ACO algorithm as fitness value in order to lead the optimization of particle swarm, we can obtain the optimal solution as well as better convergence speed and effect. Finally, the model and problem solving process were programmed in the C++ language. Intensive computational experiments were done on cases in PSPLIB. The result shows that with the iteration of PSO algorithm, both the performance and convergence of ACO algorithm are improved.