Volume 3, Issue 1

In early 2013, Ministry of Railways (MOR) is dismantled into administrative and business arms. To tackle with economic performance setbacks and huge financial debt, Chinese Railway Group Corporation (CRGC), who is in charge of business operations, determined to make product innovation for express freight so as to provide the market with value-added logistical services and increase its revenue. This paper aims to analyze the necessity and feasibility of developing innovative express product for CRGC. Under the condition of heavy accumulated debt pressure and continuous economic losses, it is imperative for Chinese railway to increase revenue through the introduction of novel express freight services. Based on complete transportation product theory, this paper summarizes the temporal-and-spatial characteristics of modern logistics, analyzes the prospect of supplying express freight services, and applies Express Freight Network Design Model to identify key factors for express freight product supply. In order to improve service quality of express freight product, it is necessary to optimize transportation organization, put forward market-oriented customized products, and improve informationization standard.

Benevolent and aggressive cross-efficiency evaluation methods are the improvement of the cross-efficiency evaluation method. They merely maximize or minimize the efficiency of the composite unit constructed by evaluated decision-making units while maintaining the optimal efficiency of the decision-making unit under evaluation. The two methods completely ignore the self-evaluation efficiency of evaluated unit and the good relationship among decision-making units. To solve the above drawbacks, the authors consider the efficiency score of the decision-making unit as an interval number and propose a more reasonable interval number. On the basis of the interval efficiency, the authors provide the benevolent and aggressive DEA cross-efficiency evaluation models based on the good relationship among all decision-making units. Finally, a numerical example is provided to illustrate the proposed method.

This paper presents the dynamic fuzzy clustering method to solve the multi-producers to multi-customers large-scale distribution problem. The proposed method includes three phases: Static clustering, order processing, and dynamic clustering. Based on the distances among customers, k -means method is used to generate the static clusters. The service priorities of each producer serving the static customer groups are ranked according to the distance performance. In the case of fluctuant customer orders, order processing can divide customer orders into several consecutive periods. After the above two phases, the fuzzy clustering technique is applied to further conduct dynamic clustering based on the customer order attributes. Similarly, the service priorities of generated dynamic customer groups will be ranked according to the time attributes of orders. Finally, by the real case, the authors obtain the conclusion that using the proposed method, the total cost of the producer is reduced by about 35%, and the vehicle loading rates are almost above 95%.

This paper studies the closed-loop supply chain decision problem in which the original manufacturer allows the third-party remanufacturer to remanufacture under patent protection. In the two cycle mode, the authors discuss the pricing decision problem of the original manufacturer, the retailer, and the third-party remanufacturer in centralized and decentralized decision-making cases. The authors obtain the optimal sale price and wholesale price of new products and remanufactured products in two cases, and the optimal recycling rate of used products in centralized decision-making case. Finally, the authors carry out the corresponding numerical simulation of the pricing decision.

This paper studies the control variate method for pricing interest rate derivatives driven by the LIBOR market model. Several control variates are constructed based on distinctive approximations for the LIBOR market model. Numerical results show the great efficiency of our methods. The idea in this paper can also be extended to price other interest rate derivatives under the LIBOR market model, such as Swaptions, Caps , some path dependent interest rate derivatives, and so forth.

In the situation of indirect network effect, this paper mainly studies the optimal extended warranty price. First, the characteristics of the extended warranty price are discussed. Next, the optimal extended warranty price model is advanced. From the model, the authors can draw that the influence factors mainly include the producer and consumers’ risk preferences, the incompatible degree of the producer’s maintenance technology, the extended warranty period, the producer and consumers’ per-occasion maintenance cost. Finally, the authors carry the simulation method to indicate their influence relation. The results have theoretical significance for the automobile producer to ensure the optimal extended warranty price.

This paper considers several parallel machine scheduling problems with controllable processing times, in which the goal is to minimize the makespan. Preemption is allowed. The processing times of the jobs can be compressed by some extra resources. Three resource use models are considered. If the jobs are released at the same time, the problems under all the three models can be solved in a polynomial time. The authors give the polynomial algorithm. When the jobs are not released at the same time, if all the resources are given at time zero, or the remaining resources in the front stages can be used to the next stages, the offline problems can be solved in a polynomial time, but the online problems have no optimal algorithm. If the jobs have different release dates, and the remaining resources in the front stages can not be used in the next stages, both the offline and online problems can be solved in a polynomial time.

With China’s economic slowdown and port low-level repeated construction, China ports are facing the problem of overheated investment. In this paper, using the port supply-demand balance and comprehensive cost as the two main optimization goals, the ecological carrying capacity and the port profit-loss as the constraints, the port multi-period investment decision optimization model is built up by means of dynamic programming. Sustainable development ability about port supply-demand matching and ecological carrying capacity are considered into the decision-making model, which is used to solve the existing literature disadvantage of port investment planning decision based on operation efficiency and benefit. It helps to prevent the port resources waste and ecological environment destruction, and has the reality instruction significance.

Heavy ordered weighted averaging (OWA) operator is important for characterizing the decision maker’s attitudinal character in multi-attribute decision making (MADM) problem with part or total ignorance. This paper develops a new method based on heavy OWA operator to solve the MADM problem in which the attributes are characterized by some trapezoidal intuitionistic fuzzy numbers (TrIFNs). TrIFN, as a special kind of intuitionistic fuzzy set defined on the real numbers, is useful for characterizing the ill-known quantity in reality. Firstly, the operation laws and the cut sets concept for TrIFNs are introduced. Then the authors define the membership and non-membership average indexes. A new ranking method is developed on the basis of the two indexes. In the proposed decision model, the multi-attribute TrIFN values of the candidates are aggregated by the Heavy OWA operator, and ranked by their membership and non-membership average indexes. Lastly, the authors illustrate the proposed method by a numerical example which implies the practicality and effectiveness of the method.