Band 5, Heft 2

In the pallet pool system, the differentiation of palletized freight volumes in different regions and seasonal transport of certain goods lead to the imbalance of pallets distribution among regions. It is necessary to improve the utilization of pallets through dispatching. The paper analyzes the factors which affect empty pallets dispatching, it includes carbon emission, transportation time and pallet type based on the pallet pool mode of enterprise alliance. On this basis, the optimization model is established with the goal of minimum total dispatching cost. Then, according to the different influences of railway and highway in transportation cost, the dispatching scheme is analyzed and the transportation mode of empty pallets dispatching is determined. Considering the characteristics of model, Cplex is used to solve it. Finally, a case is used to verify the feasibility and superiority of reasonable empty pallets dispatching in different transportation modes, and the transport characteristics of two transportation modes are analyzed. Moreover, the costs of pallets leasing and dispatching are compared.

In this paper, regulatory and optimum programming model has been adopted. Considering the costs of emission reduction, supervision and penalty, we went all out to analyze the optimal decision of cost efficiency of regulators when implementing these three policy instruments: carbon emission standards, carbon emission trading permissions, and carbon taxes as well. Its result has indicated: In strict accordance with control target of total carbon emissions, regulators are willing to render social and economic cost able to achieve the goal of optimal cost efficiency by regulating carbon emission standards and supervising marginal cost caused by variations in the probability; fortunately, under the conditions of low supervisory cost and certain criteria which is met, the implementation of carbon emission trading permissions could provide social and economic cost with opportunities to realize that objective; through comparative analysis, carbon emission trading permissions have the advantages of higher efficiency than carbon emission standards on the premise of incomplete information. During the implementation of carbon taxes strategy, when there exists uncertainty information in the enterprises reduction behaviors, the condition which enterprises can fully comply with is the tax rate level is not higher than marginal penalty function; the tax rate level of enterprises perfect compliance ought not to be lower than the division of marginal penalty cost and marginal supervisory cost. The optimal strategy of enterprises imperfect compliance is that regulators varying the marginal cost of emission standards is equal to varying that of supervisory probability.

The analytic hierarchy process (AHP) is used widely for analyzing decisions made in various real-world applications. Its basic idea is to construct a hierarchy of concepts encountered in a given decision problem and to choose the best alternative according to pairwise comparison matrices given by the decision maker. Under the assumption of fully rational economics, a reasonable decision should be consistent. It becomes an important issue on how to analyze and ensure the consistency of comparison matrices together with the judgments of the decision maker. The main objectives of the present paper are threefold. First, we review the basic idea and methods used to define the consistency and the transitivity of multiplicative reciprocal matrices, additive reciprocal matrices and comparison matrices with fuzzy interval and triangular fuzzy numbers. The existing controversy behind the applications of fuzzy set theory to the AHP in the literature is presented. Second, the consistency of the collective comparison matrices in group decision making based on AHP and fuzzy AHP is further analyzed. We point out that the weak consistency of preference relations with fuzzy numbers in fuzzy AHP and group decision making should be investigated comprehensively. Third, under the consideration of the vagueness in the process of evaluating the judgements, a new concept of fuzzy consistency of comparison matrices in the AHP is given.

This paper proposes a group decision making method based on entropy of neutrosophic linguistic sets and generalized single valued neutrosophic linguistic operators. This method is applied to solve the multiple attribute group decision making problems under single valued neutrosophic liguistic environment, in which the attribute weights are completely unknown. First, the attribute weights are obtained by using the entropy of neutrosophic linguistic sets. Then three generalized single valued neutrosophic linguistic operators are introduced, including the generalized single valued neutrosophic linguistic weighted averaging (GSVNLWA) operator, the generalized single valued neutrosophic linguistic ordered weighted averaging (GSVNLOWA) operator and the generalized single valued neutrosophic linguistic hybrid averaging (GSVNLHA) operator, and the GSVNLWA and GSVNLHA operators are used to aggregate information. Furthermore, similarity measure based on single valued neutrosophic linguistic numbers is defined and used to sort the alternatives and obtain the best alternative. Finally, an illustrative example is given to demonstrate the feasibility and effectiveness of the developed method.

Asset allocation is an important issue in finance, and both risk and return are its fundamental ingredients. Rather than the return, the measure of the risk is complicated and of controversy. In this paper, we propose an appropriate risk measure which is precisely a convex combination of mean semi-deviation and conditional value-at-risk. Based on this risk measure, investors can trade-off flexibly between the volatility and the loss to tackle the incurring risk by choosing different convex coefficients. As the presented risk measure contains nonsmooth term, the asset allocation model based on it is nonsmooth. To employ traditional gradient algorithms, we develop a uniform smooth approximation of the plus function and convert the model into a smooth one. Finally, an illustrative empirical study is given. The results indicate that investors can control risk efficiently by adjusting the convex coefficient and the confidence level simultaneously according to their perceptions. Moreover, the effectiveness of the smoothing function proposed in the paper is verified.

This paper deals with a discrete-time Geo/Geo/1 queueing system with working breakdowns in which customers arrive at the system in variable input rates according to the states of the server. The server may be subject to breakdowns at random when it is in operation. As soon as the server fails, a repair process immediately begins. During the repair period, the defective server still provides service for the waiting customers at a lower service rate rather than completely stopping service. We analyze the stability condition for the considered system. Using the probability generating function technique, we obtain the probability generating function of the steady-state queue size distribution. Also, various important performance measures are derived explicitly. Furthermore, some numerical results are provided to carry out the sensitivity analysis so as to illustrate the effect of different parameters on the system performance measures. Finally, an operating cost function is formulated to model a computer system and the parabolic method is employed to numerically find the optimum service rate in working breakdown period.