气候政策的经济环境效应分析与比较—基于碳税、许可交易和总量控制的动态微分博弈

基于产品差别化假设,建立双寡头动态微分博弈模型,比较碳税和许可交易以及总量控制3种气候政策的经济环境效应.研究发现,不同气候政策对两国的经济效应不同.进一步研究还发现,在企业产品差别化竞争时,从碳排放流量来看,碳税政策和许可交易政策与总量控制政策之间没有严格的优劣之分;碳排放存量对碳税政策最敏感.从碳存量对政策的边际影响来看,许可交易政策与总量控制政策是相同的,而碳税政策与之相反.当两国生产的产品完全同质时,从均衡碳排放流量和碳排放存量来看,许可交易政策最优,总量控制政策次之,碳税政策最差.若政府单纯以控制碳排放量为目的,许可交易政策是最佳选择.     

A parametric linear complementarity technique for the computation of equilibrium prices in a single commodity spatial model

This paper presents a parametric linear complementarity technique for the computation of equilibrium prices in a single commodity spatial model. We first reformulate the model as a linear complementarity problem and then apply the parametric principal pivoting algorithm for its solution. This reformulation leads to the study of an arc—arc weighted adjacency matrix associated with a simple digraph having weights on the nodes. Several basic properties of such a matrix are derived. Using these properties, we show how the parametric principal pivoting algorithm can be greatly simplified in this application. Finally, we report some computational experience with the proposed technique for solving some large problems.     

A model for the economic evaluation of master city plans: a pilot study of Västerås,Sweden

The paper introduces the framework, problems addressed, objective function, types of variables and so on for a model designed to facilitate the economic evaluation of master city plans. The model presented here has been used in a pilot study of the city of Västerås, Sweden. It consists of three main parts, data, results and method. Some conclusions are drawn.     

Bounds for the tail distribution in a queue with a superposition of general periodic Markov sources: theory and application

An efficient yet accurate estimation of the tail distribution of the queue length has been considered as one of the most important issues in call admission and congestion controls in ATM networks. The arrival process in ATM networks is essentially a superposition of sources which are typically bursty and periodic either due to their origin or their periodic slot occupation after traffic shaping. In this paper, we consider a discrete-time queue where the arrival process is a superposition of general periodic Markov sources. The general periodic Markov source is rather general since it is assumed only to be irreducible, stationary and periodic. Note also that the source model can represent multiple time-scale correlations in arrivals. For this queue, we obtain upper and lower bounds for the asymptotic tail distribution of the queue length by bounding the asymptotic decay constant. The formulas can be applied to a queue having a huge number of states describing the arrival process. To show this, we consider an MPEG-like source which is a special case of general periodic Markov sources. The MPEG-like source has three time-scale correlations: peak rate, frame length and a group of pictures. We then apply our bound formulas to a queue with a superposition of MPEG-like sources, and provide some numerical examples to show the numerical feasibility of our bounds. Note that the number of states in a Markov chain describing the superposed arrival process is more than 1.4 × 10⁸⁸. Even for such a queue, the numerical examples show that the order of the magnitude of the tail distribution can be readily obtained.     

Analysis of the expected discounted penalty function for a general jump-diffusion risk model and applications in finance

In this paper, we extend the Cramér-Lundberg risk model perturbed by diffusion to incorporate the jumps of surplus investment return. Under the assumption that the jump of surplus investment return follows a compound Poisson process with Laplace distributed jump sizes, we obtain the explicit closed-form expression of the resulting Gerber-Shiu expected discounted penalty (EDP) function through the Wiener-Hopf factorization technique instead of the integro-differential equation approach. Especially, when the claim distribution is of Phase-type, the expression of the EDP function is simplified even further as a compact matrix-type form. Finally, the financial applications include pricing barrier option and perpetual American put option and determining the optimal capital structure of a firm with endogenous default.     

A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling

Due to the implementation of government legislation, social responsibility, environmental concern, economic benefits and customer awareness the industries are under a great pressure not only to provide environmentally friendly products but also to take back the product after its use. The issue in reverse logistics is to take back the used products, either under warranty or at the end of use or at the end of lease, so that the products or its parts are appropriately disposed, recycled, reused or remanufactured. In order to overcome this issue, it is necessary to setup a logistics network for arising goods flow from end users to manufacturers. In this study, the optimum usage of secondary lead recovered from the spent lead–acid batteries for producing new battery is presented. The disposal in surface or sewage water or land of liquid content of the lead–acid batteries is strictly restricted. Because of the need for environmental protection and the lack of considerable lead resources, the spent batteries treatment and lead recovery are becoming crucial now-a-days. The objective of this paper is to develop a multi echelon, multi period, multi product closed loop supply chain network model for product returns and the decisions are made regarding material procurement, production, distribution, recycling and disposal. The proposed heuristics based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model (MILP). Finally the computational results obtained through GA are compared with the solutions obtained by GAMS optimization software. The solution reveals that the proposed methodology performs very well in terms of both quality of solutions obtained and computational time.     

Global properties of a general dynamic model for animal diseases: A case study of brucellosis and tuberculosis transmission

Animal diseases such as brucellosis and tuberculosis can be transmitted through an environmentally mediated mechanism, but the topics of most modeling work are based on infectious contact and direct transmission, which leads to the limited understanding of the transmission dynamics of these diseases. In this paper, we propose a new deterministic model which incorporates general incidences, various stages of infection and a general shedding rate of the pathogen to analyze the dynamics of these diseases. Under the biologically motivated assumptions, we derive the basic reproduction number _R0$R_0$, show the uniqueness of the endemic equilibrium, and prove the global asymptotically stability of the equilibria. Some specific examples are used to illustrate the utilization of our results. In addition, we elaborate the epidemiological significance of these results, which are very important for the prevention and control of animal diseases.     

Time delay factor can be used as a key factor for preventing the outbreak of a disease—Results drawn from a mathematical study of a one season eco-epidemiological model

Chatterjee and Chattopadhyay [Role of migratory bird population in an simple eco-epidemiological model, Math. Comp. Model. Dyn. Syst., in press] proposed and analyzed a one season eco-epidemiological model of susceptible and infective prey together with their predators. In such systems, time lags due to the gestation of the infective prey are of importance. In this paper we modify and analyze their model by taking this factor into consideration. Our analysis shows that the outbreak of the disease can be controlled by a careful and suitable increment of the time lag factor. Moreover, to preserve the stability of the coexisting equilibrium, the time lag factor plays an important role. To substantiate our analytical results, extensive numerical simulations are performed for a hypothetical set of parameter values.     

Algorithm for a general discrete k-out-of-n: G system subject to several types of failure with an indefinite number of repairpersons

A discrete k-out-of-n: G system with multi-state components is modelled by means of block-structured Markov chains. An indefinite number of repairpersons are assumed and PH distributions for the lifetime of the units and for the repair time are considered. The units can undergo two types of failures, repairable or non-repairable. The repairability of the failure can depend on the time elapsed up to failure. The system is modelled and the stationary distribution is built by using matrix analytic methods. Several performance measures of interest, such as the conditional probability of failure for the units and for the system, are built into the transient and stationary regimes. Rewards are included in the model. All results are shown in a matrix algorithmic form and are implemented computationally with Matlab. A numerical example of an optimization problem shows the versatility of the model.