Game theory approach to optimal capital cost allocation in pollution control

This paper tries to integrate game theory, a very useful tool to resolve conflict phenomena, with optimal capital cost allocation issue in total emission control. First the necessity of allocating optimal capital costs fairly and reasonably among polluters in total emission control was analyzed. Then the possibility of applying game theory to the issue of the optimal capital cost allocation was expounded. Next the cooperative N person game model of the optimal capital cost allocation and its solution ways including method based on Shapley value, least core method, weak least core methods, proportional least core method, CGA method, MCRS method and so on were delineated. Finally through application of these methods it was concluded that to apply game theory in the optimal capital cost allocation issue is helpful to implement the total emission control planning schemes successfully, to control pollution effectively, and to ensure sustainable development.

Optimal allocation of watershed management cost among different water users

The issue of water scarcity highlights the importance of watershed management. A sound watershed manage- ment should make all water users share the incurred cost. This study analyzes the optimal allocation of watershed management cost among different water users. As a consumable, water should be allocated to different users the amounts in which their marginal utilities (MUs) or marginal products (MPs) of water are equal. The value of MUs or MPs equals the water price that the watershed manager charges. When water is simultaneously used as consumable and non- consumable, the watershed manager produces the quantity of water in which the sum of MUs and/or MPs for the two types of uses equals the marginal cost of water production. Each water user should share the portion of watershed management cost in the percentage that his MU or MP accounts for the sum of MUs and/or MPs. Thus, the price of consumable water does not equal the marginal cost of water production even if there is no public good.

Resource Allocation Using SPA Based on Different Cost Functions in Elastic Optical Networks

Routing, modulation and spectrum allocation in elastic optical networks is a problem aiming at increasing the capacity of the network. Many algorithms such as shortest path algorithm can be used as the routing section of this problem. The efficiency of these algorithms is partly based on how the cost of each link is defined. In this study, we considered several basic metrics in cost of network links and compared their effects on the network capacity. In particular, the static costs and the dynamic costs were evaluated and compared. For dynamic scenarios, compared to static scenarios, at least one additional factor, the usage of the links, was added. We further considered a new factor that is based on probability of accommodating the signal at a given time in any given link. The results show that, among them, the shortest path algorithm provides the least blocking probability when the cost is a combination of link length and the abovementioned possibility/usage of the link.

Multi-QoS Guaranteed Resource Allocation for Multi-Services Based on Opportunity Costs

To meet the booming development of diversified services and new applications in the future, the fifth-generation mobile conmmnication system （5G） has arisen. Resources are increasingly scarce in the @namic time-varying of 5G networks. Allocating resources effectively and ensuring quality of service （QoS） requirements of multi-seiwices come to be a research focus. In this paper, we utilize effective capacity to build a utility function with multi-QoS metrics, including rate, delay bound and packet loss ratio. Taking advantage of opportunity cost （OC）, we also propose a multi-QoS guaranteed resource allocation algm＇ithm for multi-services to consider the future condition of system. In the algorithm, according to different business characteristics and the theory of OC, we propose different selection conditions for QoS users and best effort （BE） users to choose more reasonable resources. Finally, simulation results show that our proposed algorithm achieves superior system utility and relatively better fairness in multi-service scenarios.

Allocation of congestion relief cost based on flow change on the congested facilities

Congestion management in an electricity market is introduced in this paper and a new method of allocating congestion cost to transactions is proposed. The proposed method is a two-step process, in which the total congestion cost is firstly allocated to congested facilities and then to each transaction involved. The cost of relieving a congested facility allocated to each transaction is proportional to the power flow change on the congested facility caused by the transaction. The more the power flow change is on the congested facility caused by the transaction, the deeper the degree of involvement by the transaction. Therefore, cutting down the magnitudes of such transactions contributes to relieving congestion. Test results on a 5-bus system indicate that the proposed method can reflect reasonably the degree of involvement by each transaction in the congestion and provide correct price signals contributing to relieving congestion.

Design of cost allocation rule for joint replenishment with controllable lead time

To encourage retailers to form cooperative alliances to jointly replenish inventory,considering that the supplier provides a flexible lead time and quantity discount to retailers,a model of average total cost per unit time of periodic joint replenishment is constructed,and an approximate algorithm,which can satisfy the requirement of any given precision,is given.The cost allocation rule in the core of the joint replenishment game is designed based on the cooperative game theory.The numerical experiment results show that the proposed algorithm can quickly solve the joint replenishment problem when the item number is not greater than 640.The retailer's cost saving rate is always greater than 0,and it increases with the increase in quantity discount and fixed cost after adopting the given cost allocation rule.With the increase in the safety stock level,the retailer's cost saving rate increases first and then decreases;and the retailer's cost saving rate increases with the increase in the size of the alliance,but it decreases as the number of product category increases.The proposed cost allocation rule can reduce the retailer's cost up to 20%,which is conducive to forming a cooperative coalition.

Power flow tracing based method for allocation of transmission service cost to transactions

Based on the concepts of objective fact and subjective desire proposed in this paper, the problems that exist in the nodal injections-based and transaction-based transmission service allocation scheme are pointed out. To get around the problems above, a novel transmission service allocation scheme is proposed which considers the power flow distribution and the transaction impact on the system simultaneously so that the issues of “Cross-subsidies” and “Counter flow” can be avoided. The principle of the scheme is illustrated using two simple networks with 7 cases. The results show that the proposed scheme can satisfy the properties necessary for the development and growth of the electricity market.

Allocation of fixed transmission cost based on power flow tracing algorithm

In the electricity market, charging based on the traditional spot electricity price often results in the payment imbalance of electric network, and goes against the development of the power system. So, it is necessary to modify the spot price. The key of the modification lies in how to calculate the fixed unit transmission cost of each node, that is how to allocate the fixed transmission cost to users.To solve this problem, we develop a power flow tracing algrithm to modify the spot price. We put forward a path searching method based on the graph theory after studying the fundamental principle of power flow tracing and apply the method to the downstream tracing algorithm and upstream tracing algorithm according to the proportional distribution principle. Furthermore, to improve the computational efficiency of the algorithm, we introduce the branch expunction method to optimize the node order. By using the result of power flow tracing to get fixed node transmission cost and introducing it to modify the spot price, we obtain the synthetical price.The application to a 5-bus system prove the algorithm feasible.

Objective function of cost in optimal tolerance allocation

An objective function model is proposed for cost in optimizing and allocating tolerance with consideration of manufacturing conditions. With the fuzzy comprehensive evaluation method,a manufacturing difficulty coefficient is derived,which takes into account of several factors affecting the manufacturing cost,including the forming means of the blank,size,machining surface features,operator’s skills and machinability of materials. The coefficient is then converted into a weight factor used in the inversed square model representing the relationship between the cost and tolerance,and,hence,an objective function for cost is established in optimizing and allocating tolerance. The higher is the manufacturing difficulty coefficient,the higher is the relative manufacturing cost and the higher is the weight factor of the tolerance allocation,which indicates the increase of the tolerance’s effects on the total manufacturing cost and,therefore,a larger tolerance should be allocated. The computer-aided tolerance allocation utilizing this model makes it more convenient,accurate and practicable.

Review of Methods to Calculate Congestion Cost Allocation in Deregulated Electricity Market

With maturing deregulated environment for electricity market, cost of transmission congestion becomes a major issue for power system operation. Uniform Marginal Price and Locational Marginal Price (LMP) are the two practical pricing schemes on energy pricing and congestion cost allocation, which are based on different mechanisms. In this paper, these two pricing schemes are introduced in detail respectively. Also, the modified IEEE-14-bus system is used as a test system to calculate the allocated congestion cost by using these two pricing schemes.

User Association and Power Allocation for UAV-Assisted Networks: A Distributed Reinforcement Learning Approach

Unmanned aerial vehicles(UAVs)can be employed as aerial base stations(BSs)due to their high mobility and flexible deployment.This paper focuses on a UAV-assisted wireless network,where users can be scheduled to get access to either an aerial BS or a terrestrial BS for uplink transmission.In contrast to state-of-the-art designs focusing on the instantaneous cost of the network,this paper aims at minimizing the long-term average transmit power consumed by the users by dynamically optimizing user association and power allocation in each time slot.Such a joint user association scheduling and power allocation problem can be formulated as a Markov decision process(MDP).Unfortunately,solving such an MDP problem with the conventional relative value iteration(RVI)can suffer from the curses of dimensionality,in the presence of a large number of users.As a countermeasure,we propose a distributed RVI algorithm to reduce the dimension of the MDP problem,such that the original problem can be decoupled into multiple solvable small-scale MDP problems.Simulation results reveal that the proposed algorithm can yield lower longterm average transmit power consumption than both the conventional RVI algorithm and a baseline algorithm with myopic policies.

Multi-robot task allocation for exploration

The problem of allocating a number of exploration tasks to a team of mobile robots in dynamic environments was studied. The team mission is to visit several distributed targets. The path cost of target is proportional to the distance that a robot has to move to visit the target. The team objective is to minimize the average path cost of target over all targets. Finding an optimal allocation is strongly NP-hard. The proposed algorithm can produce a near-optimal solution to it. The allocation can be cast in terms of a multi-round single-item auction by which robots bid on targets. In each auction round, one target is assigned to a robot that produces the lowest path cost of the target. The allocated targets form a forest where each tree corresponds a robot’s exploring targets set. Each robot constructs an exploring path through depth-first search in its target tree. The time complexity of the proposed algorithm is polynomial. Simulation experiments show that the allocating method is valid.

Optimal Resource Allocation and Quality of Service Prediction in Cloud

In the present scenario,cloud computing service provides on-request access to a collection of resources available in remote system that can be shared by numerous clients.Resources are in self-administration;consequently,clients can adjust their usage according to their requirements.Resource usage is estimated and clients can pay according to their utilization.In literature,the existing method describes the usage of various hardware assets.Quality of Service(QoS)needs to be considered for ascertaining the schedule and the access of resources.Adhering with the security arrangement,any additional code is forbidden to ensure the usage of resources complying with QoS.Thus,all monitoring must be done from the hypervisor.To overcome the issues,Robust Resource Allocation and Utilization(RRAU)approach is developed for optimizing the management of its cloud resources.The work hosts a numerous virtual assets which could be expected under the circumstances and it enforces a controlled degree of QoS.The asset assignment calculation is heuristic,which is based on experimental evaluations,RRAU approach with J48 prediction model reduces Job Completion Time(JCT)by 4.75 s,Make Span(MS)6.25,and Monetary Cost(MC)4.25 for 15,25,35 and 45 resources are compared to the conventional methodologies in cloud environment.

Optimal Rate Allocation Based on Cross-Layer Design and End-to-End Congestion Control in WCDMA Networks

In this paper, a novel idea for rate allocation combining both vertical coupling and horizontal coupling constraints is proposed, and a unified utility function to balance two paradoxical issues: efficiency and fairness, revenue and cost is elaborated in WCDMA networks. Then, the optimal rate allocation problem is formulated as a network utility maximization(NUM) model based on cross-layer design and end-to-end congestion control, aiming at exploring the impacts of wired networks and the characteristics of radio access networks(RANs) on rate allocation. Furthermore, a distributed algorithm is derived, which can effectively match load states between RANs and wired networks, followed by a detailed illustration of the practical implementations. Numerical results demonstrate a signifi cant performance improvement in the end-to-end throughput.

Photosynthetic Carbon Gain, Allocation and Resources-Use Efficiency in Invasive Eupatorium Adenophorum and Its Native Congener E. Japonicum under Different Light and Nutrient Conditions

Invasion is often facilitated by high resources availabilities and suppressed under low resources habitats. However, a number of invasive plants can successfully establish and dominate in resource-poor and （or） the understory of closed forests, indicating the plant＇s performances are habitats-dependent and species-specific. It is therefore necessary to explore the ecophysiological characteristics associated invasiveness for one invasive species across multiple resources availabilities whilst taking the relatedness into these comparative studies. In this study, invasive Eupitorium adenophorum and its native congener E. japonicum grew under different resource gradients in terms of light levels and soil nitrogen additions to identify the functional significance morphological and physiological traits associated closely with invasion and to examine their comparative responses. Photosynthetic carbon gain, biomass allocation and resource-use efficiency are evaluated in this pot experiment. Across treatments, E. adenophorum exhibited consistently higher values for most of the morphological variables including plant stature, relative growth rate （RGR）, leaf root ratio （LRR）, leaf area ratio （LAR）, total leaf area, and lower root： shoot ratio （RSR）. Significantly higher Pmax corresponded with higher photosynthetic nitrogen use efficiency （PNUE） and photosynthetic energy use efficiency （PEUE） especially in low light and （or） unfertile condition. Higher Gs and Pmax but lower photosynthetic water use efficiency （WUE） indicated the trade-off relationship between WUE and PNUE for E. adenophorum. Final biomasses were higher for E. adenophorum in nutrient and（or） light limited conditions, in which higher leaf construction cost（CC） compared with E. japonicum could be over-compensated by its significantly higher assimilation rates. The effects of light levels on these plant attributes were stronger than soil nutrient contents. The responses of these two congeneric species to light and nitrogen availabilities were similar, but the differences were magnified in resources limited conditions, indicating the better performancer at acquiring and at using limited resources of E. adenophorum over its co-occurring native flora. Our study presented the distinctive advantages of E. adenophorum in resources-poor environments, indicating conventional strategy of managing resources levels to control the invasion and expending of exotic species may not be as effective as expected.

基于New Cost DEA模型的棉花生产成本效率评价与分析——以新疆为例

运用New Cost DEA模型对新疆2010年22个产棉区的成本效率进行测算,结果显示:仅有1个产棉区是成本效率有效单元,其他21个产棉区都属于成本效率弱有效,其中配置效率是影响成本效率弱有效的重要原因。通过对各棉花产区的实际成本分解,可以看出除了配置效率原因导致成本增加是实际成本上升的主要原因外,技术效率和价格原因也导致了成本增加。为进一步降低实际成本,应从优化投入要素的配置结构、减少生产技术效率的冗余和降低生产投入要素的采购价格方面着手来降低成本,提高产棉区的成本效率。

市场化程度对自主创新配置效率的影响——基于Cost-Malmquist指数的高技术产业行业面板数据分析

在中国经济转型特定的制度环境中,内、外开放两种不同的市场导入机制对创新资源配置效率的影响完全不同。本文从创新结构红利的成本视角采用三阶段Cost-Malmquist指数法将中国高技术产业整体、内资和外资部门的自主创新资源配置效率拆分为分配效率(企业家要素组合的效率)和价格前沿的变化,得出:我国内资部门企业家要素组合能力不断提升,却面临更加扭曲的要素价格约束,导致创新资源配置效率提高受限并影响了结构红利的获得。用动态面板数据模型验证市场化程度对自主创新配置效率的影响得到:第一,政府的税收掠夺显著增强整体和内资部门长、短期的成本约束,使要素价格逼近边际成本前沿面,提高了创新资源配置效率,但以企业家组合资源效率的损失为代价;政府直接资金扶持仅具有短期效应,长期则加大要素价格扭曲、负向影响创新资源配置效率;第二,较之于对外开放,对内开放程度显著缓解了内资部门要素价格扭曲,使要素价格逼近边际成本前沿面,有利提高自主创新资源配置效率,并具有长期效应。对外开放程度只能短期提高企业家的要素组合效率、无长期效应;第三,金融、信贷市场和技术市场发育程度无论长、短期均显著缓解要素市场价格扭曲、使要素价格逼近边际成本前沿面,显著提升企业家的要素组合效率,提高了自主创新配置效率。

Optimal scheduling of flexible grid-side resources and auxiliary service cost allocation model considering renewable-energy penetration

Renewable energy has penetrated power grid enterprises on a large scale.Due to the intermittency and volatility of renewable energy generation,it is necessary to build new flexible grid-side resources to ensure the safe and stable operation of the power grid,which will cause great pressure on cost allocation for power grid enterprises.This article considers four types of flexible grid-side resources and constructs a dual-level configuration optimization model for flexible grid-side resources under the penetration of renewable energy.Based on the configuration results,the cost scale of flexible grid-side resources is estimated and an improved ancillary service cost allocation model based on the Shapley value method is proposed to smooth the allocation of ancillary service costs in the cost of flexible grid-side resources between the two main bodies of renewable energy and load.The calculation results show that,when the penetration rate of renewable-energy power is 30%and 35%,respectively,the cost of flexible grid-side resources is 9.606 billion yuan and 21.518 billion yuan,respectively.The proportion of ancillary service costs allocated to load is relatively high-about five times that of the ancillary service costs allocated to renewable energy-and the higher the penetration rate of renewable energy,the higher the proportion of ancillary service costs allocated to renewable energy.

Application Research of Oil Development Costs in Reservoir Management

Based on oil development costs, the application research in the technical and economic limits calculation of oil development and the production optimal allocation to all the oilfields, was finished. At the same time, according to the regression of real development costs, a new method for oil well economic water cut and oil well economic rate are set up, the production optimal allocation is developed with satisfactory results.

Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located inremote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and taskscheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud isemployed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the currentresearch work develops a Cost-Effective Optimal Task Scheduling Model(CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) modelis used in the proposed work for hybrid clouds. Moreover, the algorithm workson the basis of multi-intentional task completion process with optimal resourceallocation. The model was successfully simulated to validate its effectivenessbased on factors such as processing time, make span and efficient utilization ofvirtual machines. The results infer that the proposed model outperformed theexisting works and can be relied in future for real-time applications.