Optimal allocation of carbon credits to emitting agents in a carbon economy

Reduction of carbon emissions is of paramount importance in the context of global warming. Countries and global companies are now engaged in understanding systematic ways of achieving well defined emission targets. In fact, carbon credits have become significant and strategic instruments of finance for countries and global companies. In this paper, we formulate and suggest a solution to the carbon allocation problem, which involves determining a cost minimizing allocation of carbon credits among different emitting agents. We address this challenge in the context of a global company which is faced with the challenge of determining an allocation of carbon credit caps among its divisions in a cost effective way. The problem is formulated as a reverse auction problem where the company plays the role of a buyer or carbon planning authority and the different divisions within the company are the emitting agents that specify cost curves for carbon credit reductions. Two natural variants of the problem: (a) with unlimited budget and (b) with limited budget are considered. Suitable assumptions are made on the cost curves and in each of the two cases we show that the resulting problem formulation is a knapsack problem that can be solved optimally using a greedy heuristic. The solution of the allocation problem provides critical decision support to global companies engaged seriously in green programs.

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Tradeoff of average service cost and average delay for the state dependent M/M/1 queue

The optimal tradeoff between average service cost rate and average delay, is addressed for a M/M/1 queueing model with queue-length dependent service rates, chosen from a finite set. We provide an asymptotic characterization of the minimum average delay, when the average service cost rate is a small positive quantity V more than the minimum average service cost rate required for stability. We show that depending on the value of the arrival rate, the assumed service cost rate function, and the possible values of the service rates, the minimum average delay either a) increases only to a finite value, b) increases without bound as log(1/V), or c) increases without bound as 1/V, when V down arrow 0. We apply the analysis to a flow-level resource allocation model for a wireless downlink. We also investigate the asymptotic tradeoff for a sequence of policies which are obtained from an approximate fluid model for the M/M/1 queue.

Optimization of bus allocation to depots by minimizing dead kilometers

In metropolitan cities, public transportation service plays a vital role in mobility of people, and it has to introduce new routes more frequently due to the fast development of the city in terms of population growth and city size. Whenever there is introduction of new route or increase in frequency of buses, the nonrevenue kilometers covered by the buses increases as depot and route starting/ending points are at different places. This non-revenue kilometers or dead kilometers depends on the distance between depot and route starting point/ending point. The dead kilometers not only results in revenue loss but also results in an increase in the operating cost because of the extra kilometers covered by buses. Reduction of dead kilometers is necessary for the economic growth of the public transportation system. Therefore, in this study, the attention is focused on minimizing dead kilometers by optimizing allocation of buses to depots depending upon the shortest distance between depot and route starting/ending points. We consider also depot capacity and time period of operation during allocation of buses to ensure parking safety and proper maintenance of buses. Mathematical model is developed considering the aforementioned parameters, which is a mixed integer program, and applied to Bangalore Metropolitan Transport Corporation (BMTC) routes operating presently in order to obtain optimal bus allocation to depots. Database for dead kilometers of depots in BMTC for all the schedules are generated using the Form-4 (trip sheet) of each schedule to analyze depot-wise and division-wise dead kilometers. This study also suggests alternative locations where depots can be located to reduce dead kilometers. Copyright (C) 2015 John Wiley & Sons, Ltd.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

On optimum stratification with proportional allocation for a class of pareto distributions

Cum ./LSTA_A_8828879_O_XML_IMAGES/LSTA_A_8828879_O_ILM0001.gif rule [Singh (1975)] has been suggested in the literature for finding approximately optimum strata boundaries for proportional allocation, when the stratification is done on the study variable. This paper shows that for the class of density functions arising from the Wang and Aggarwal (1984) representation of the Lorenz Curve (or DBV curves in case of inventory theory), the cum ./LSTA_A_8828879_O_XML_IMAGES/LSTA_A_8828879_O_ILM0002.gif rule in place of giving approximately optimum strata boundaries, yields exactly optimum boundaries. It is also shown that the conjecture of Mahalanobis (1952) “. . .an optimum or nearly optimum solutions will be obtained when the expected contribution of each stratum to the total aggregate value of Y is made equal for all strata” yields exactly optimum strata boundaries for the case considered in the paper.

A low cost demagnetizer with controllable cycle and adjustable level

Demagnetization to zero remanent value or to a predetermined value is of interest to magnet manufacturers and material users. Conventional methods of demagnetization using a varying alternating demagnetizing field, under a damped oscillatory or conveyor system, result in either high cost for demagnetization or large power dissipation. A simple technique using thyristors is presented for demagnetizing the material. Power consumption is mainly in the first two half-cycles of applied voltage. Hence power dissipation is very much reduced. An optimum value calculation for a thyristor triggering angle for demagnetizing high coercive materials is also presented.

Fuzzy waste load allocation model: a multiobjective approach

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Editor's message: the sunk cost fallacy of deep drilling

At the beginning of 2008, I visited a watershed, located in Karkinatam village in the state of Karnataka, South India, where crops are intensively irrigated using groundwater. The water table had been depleted from a depth of 5 to 50 m in a large part of the area. Presently, 42% of a total of 158 water wells in the watershed are dry. Speaking with the farmers, I have been amazed to learn that they were drilling down to 500 m to tap water. This case is, of course, not isolated.

Cost Sharing Mechanisms for Business Clusters with Strategic Firms

A business cluster is a co-located group of micro, small, medium scale enterprises. Such firms can benefit significantly from their co-location through shared infrastructure and shared services. Cost sharing becomes an important issue in such sharing arrangements especially when the firms exhibit strategic behavior. There are many cost sharing methods and mechanisms proposed in the literature based on game theoretic foundations. These mechanisms satisfy a variety of efficiency and fairness properties such as allocative efficiency, budget balance, individual rationality, consumer sovereignty, strategyproofness, and group strategyproofness. In this paper, we motivate the problem of cost sharing in a business cluster with strategic firms and illustrate different cost sharing mechanisms through the example of a cluster of firms sharing a logistics service. Next we look into the problem of a business cluster sharing ICT (information and communication technologies) infrastructure and explore the use of cost sharing mechanisms.

Low power pipelined TCAM employing mismatch dependent power allocation technique

This paper presents design of a Low power 256x72 bit TCAM in 0.13um CMOS technology. In contrast to conventional Match line (ML) sensing scheme in which equal power is consumed irrespective of match or mismatch, the ML scheme employed in this design allocates less power to match decisions involving a large number of mismatched bits. Typically, the probability of mismatch is high so this scheme results in significant CAM power reduction. We propose to use this technique along with pipelining of search operation in which the MLs are broken into several segments. Since most words fail to match in first segment, the search operation for subsequent segments is discontinued, resulting in further reduction in power consumption. The above architecture provides 70% power reduction while performing search in 3ns.

Optimal resource allocation in conflicts with the Lanchester linear law (2,1) model

This paper presents a detailed analysis of a model for military conflicts where the defending forces have to determine an optimal partitioning of available resources to counter attacks from an adversary in two different fronts in an area fire situation. Lanchester linear law attrition model is used to develop the dynamical equations governing the variation in force strength. Here we address a static resource allocation problem namely, Time-Zero-Allocation (TZA) where the resource allocation is done only at the initial time. Numerical examples are given to support the analytical results.

An agent based adaptive bandwidth allocation scheme for multimedia applications

Bandwidth allocation for multimedia applications in case of network congestion and failure poses technical challenges due to bursty and delay sensitive nature of the applications. The growth of multimedia services on Internet and the development of agent technology have made us to investigate new techniques for resolving the bandwidth issues in multimedia communications. Agent technology is emerging as a flexible promising solution for network resource management and QoS (Quality of Service) control in a distributed environment. In this paper, we propose an adaptive bandwidth allocation scheme for multimedia applications by deploying the static and mobile agents. It is a run-time allocation scheme that functions at the network nodes. This technique adaptively finds an alternate patchup route for every congested/failed link and reallocates the bandwidth for the affected multimedia applications. The designed method has been tested (analytical and simulation)with various network sizes and conditions. The results are presented to assess the performance and effectiveness of the approach. This work also demonstrates some of the benefits of the agent based schemes in providing flexibility, adaptability, software reusability, and maintainability. (C) 2004 Elsevier Inc. All rights reserved.

An agent based adaptive bandwidth allocation scheme for multimedia applications

Bandwidth allocation for multimedia applications in case of network congestion and failure poses technical challenges due to bursty and delay sensitive nature of the applications. The growth of multimedia services on Internet and the development of agent technology have made us to investigate new techniques for resolving the bandwidth issues in multimedia communications. Agent technology is emerging as a flexible promising solution for network resource management and QoS (Quality of Service) control in a distributed environment. In this paper, we propose an adaptive bandwidth allocation scheme for multimedia applications by deploying the static and mobile agents. It is a run-time allocation scheme that functions at the network nodes. This technique adaptively finds an alternate patchup route for every congested/failed link and reallocates the bandwidth for the affected multimedia applications. The designed method has been tested (analytical and simulation)with various network sizes and conditions. The results are presented to assess the performance and effectiveness of the approach. This work also demonstrates some of the benefits of the agent based schemes in providing flexibility, adaptability, software reusability, and maintainability. (C) 2004 Elsevier Inc. All rights reserved.

A cost effective pipelined divider for double precision floating point number

he growth of high-performance application in computer graphics, signal processing and scientific computing is a key driver for high performance, fixed latency; pipelined floating point dividers. Solutions available in the literature use large lookup table for double precision floating point operations.In this paper, we propose a cost effective, fixed latency pipelined divider using modified Taylor-series expansion for double precision floating point operations. We reduce chip area by using a smaller lookup table. We show that the latency of the proposed divider is 49.4 times the latency of a full-adder. The proposed divider reduces chip area by about 81% than the pipelined divider in [9] which is based on modified Taylor-series.