A multi-objective fuzzy optimization model for cropping structure and water resources and its method

Cropping structure has a close relationship with the optimal allocation of agricultural water resources. Based on the analysis of the relationship between agricultural water resources and sustainable development, this paper presents a multi objective fuzzy optimization model for cropping structure and water allocation, which overcomes the shortcoming of current models that only considered the economic objective,and ignored the social and environmental objectives. During the process, a new method named fuzzy deciding weight is developed to decide the objective weight. A case study shows that the model is reliable, the method is simple and objective, and the results are reasonable. This model is useful for agricultural management and sustainable development.

New approach to eliminate structural redundancy in case resource pools using α mutual information

Structural redundancy elimination in case resource pools （CRP） is critical for avoiding performance bottlenecks and maintaining robust decision capabilities in cloud computing services. For these purposes, this paper proposes a novel approach to ensure redundancy elimination of a reasoning system in CRP. By using α entropy and mutual information, functional measures to eliminate redundancy of a system are developed with respect to a set of outputs. These measures help to distinguish both the optimal feature and the relations among the nodes in reasoning networks from the redundant ones with the elimination criterion. Based on the optimal feature and its harmonic weight, a model for knowledge reasoning in CRP （CRPKR） is built to complete the task of query matching, and the missing values are estimated with Bayesian networks. Moreover, the robustness of decisions is verified through parameter analyses. This approach is validated by the simulation with benchmark data sets using cloud SQL. Compared with several state-of-the-art techniques, the results show that the proposed approach has a good performance and boosts the robustness of decisions.

FACILITATING REGIONAL SUSTAINABLE DEVELOPMENT THROUGH INTEGRATED MULTI-OBJECTIVE UTILIZATION, MANAGEMENT OF WATER RESOURCES IN THE LANCANG-MEKONG RIVER BASIN

The Lancnag Mekong River is the most important international river across China and Southeast Asia, If it is developed according to 'Great Mekong Subregional Cooperation Plan' [9] prepared by ADB, the area directly affected will be up to over 2.32 million km 2, the population over 220 million, and the natural environment, and socio-economic conditions within a large area will be greatly changed. 'Agreement on Cooperation for Sustainable Development of Mekong Basin' signed by the four riparian countries along the lower Mekong River on April 5, 1995 provides a new opportunity for sustainable development of the Basin. According to preliminary analysis, if the multipurpose utilization of the water resources is the target for carrying out integrated planning and management, and the efforts are made 1) to focus on energy exploitation on the Lancang River Mainstream and the tributaries of the lower Mekong River; 2) to build gated weirs at Tonle Sam; 3) to construct spillways at the Mekong Delta; 4) to facilitate flood dykes in big cities and on both banks of the mainstream which are concentrated with population and farmland and liable to be flooded, and 5) to strengthen networks for forecasting hydrological and meteorological conditions, then all problems such as power demand, irrigation, flood, salt water intrusion as well as acid water erosion to soil could be solved without constructing large cascaded stations and dams on the lower Mekong Mainstream. This will not only avoid input of great number of fund, large scale resettlement and land inundation, but also prevent aquatic organisms living in Mekong River from being injured due to dam construction, and promote the sustainable development of the Basin.

Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and wind.Energy resources are vital for all countries in terms of their economies and politics.As a result,selecting the optimal option for any country is critical in terms of energy investments.Every country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global warming.In the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous data.This study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp numbers.The hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective characteristics.The best-suited renewable energy alternative is discovered using the approach presented.

Collective Action in Common Pool Resource Management, Including Heterogeneity of Opportunities and Exit Options

The mechanism through which exit options and outside opportunities affect cooperation outcomes has not been well studied in the resource management literature, since a deep analysis of the concepts of “exit options” and “outside opportunities” is missing. This article analyzes these concepts across the common pool resource management literature, investigates the factors that underlie “opting out” decisions, and reviews potential ways to operationalize these concepts for empirical analysis. It also explores how the relationship of cooperation and exit options may be influenced by broad economic processes, such as economic integration.

Gini Coefficient-based Task Allocation for Multi-robot Systems With Limited Energy Resources

Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.

Resource Reconstruction Algorithms for On-demand Allocation in Virtual Computing Resource Pool

Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and the analysis of the resource status transition, the resource allocation process and the necessity of resource reconstruction are presented, l^esource reconstruction algorithms are designed to determine the resource reconstruction types, and it is shown that they can achieve the goal of resource on-demand allocation through three methodologies： resource combination, resource split, and resource random adjustment. The effects that the resource users have on the resource reconstruction results, the deviation between resources and requirements, and the uniformity of resource distribution are studied by three experiments. The experiments show that resource reconstruction has a close relationship with resource requirements, but it is not the same with current distribution of resources. The algorithms can complete the resource adjustment with a lower cost and form the logic resources to match the demands of resource users easily.

Multi-Path Routing and Resource Allocation in Active Network

An algorithm of traffic distribution called active multi-path routing (AMR)in active network is proposed. AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths. It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly. The frame of AMR includes adaptive trafficallocation model, the conception of supply bandwidth and its' allocation model, the principle ofcongestion restraint and its' model, and the implement of AMR based on multi-agents system in activenetwork. Through simulations, AMR has distinct effects on network performance. The results show AMRisa valid traffic regulation algorithm.

Critical chain construction with multi-resource constraints based on portfolio technology in South-to-North Water Diversion Project

Recently, the critical chain study has become a hot issue in the project management research field. The construction of the critical chain with multi-resource constraints is a new research subject. According to the system analysis theory and project portfolio theory, this paper discusses the creation of project portfolios based on the similarity principle and gives the definition of priority in multi-resource allocation based on quantitative analysis. A model with multi-resource constraints, which can be applied to the critical chain construction of the A-bid section in the South-to-North Water Diversion Project, was proposed. Contrast analysis with the comprehensive treatment construction method and aggressive treatment construction method was carried out. This paper also makes suggestions for further research directions and subjects, which will be useful in improving the theories in relevant research fields.

Joint Optimization of Satisfaction Index and Spectrum Efficiency with Cache Restricted for Resource Allocation in Multi-Beam Satellite Systems

Dynamic resource allocation(DRA) is a key technology to improve system performances in GEO multi-beam satellite systems. And, since the cache resource on the satellite is very valuable and limited, DRA problem under restricted cache resources is also an important issue to be studied. This paper mainly investigates the DRA problem of carrier resources under certain cache constraints. What's more, with the aim to satisfy all users' traffic demands as more as possible, and to maximize the utilization of the bandwidth, we formulate a multi-objective optimization problem(MOP) where the satisfaction index and the spectrum efficiency are jointly optimized. A modified strategy SA-NSGAII which combines simulated annealing(SA) and non-dominated sorted genetic algorithm-II(NSGAII) is proposed to approximate the Pareto solution to this MOP problem. Simulation results show the effectiveness of the proposed algorithm in terms of satisfaction index, spectrum efficiency, occupied cache, and etc.

Multi-agent Based Protection on Highly Dominated Distributed Energy Resources

Highly penetration of Distributed Energy Resources (DER) on the grid systems nowadays makes the systems grow dynamically. The system become more complex and the protection system become more complicated. The protection relay should accommodate the system changes according to the system conditions and topologies. As part of developmental aspect of Distributed Artificial Intelligent, Multi Agent System (MAS) is a challenging method for improving the intelligent properties of relay protection. This paper introduces the use of MAS approach on radial distribution system protection dominated with DER using dispersed adaptive rule-based protection supported by distributed database agent. The simulation results confirmed that the proposed algorithm can respond within 15.05 ms.

Memetic algorithm for multi-mode resource-constrained project scheduling problems

A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.

ICI Management for Efficient Radio Resource Allocation in Multi-Cell OFDMA Networks

Two Inter-cell Interference (ICI) management algorithms: Primary Interference Balancing (PIB) algorithm and Interfering Bits Loading Avoidance (IBLA) algorithm are proposed for canceling the ICI effects which the existing efficient radio resource allocation algorithms do not consider. The efficient radio resource allocation algorithm, i.e., Pre-assignment and Reassignment (PR) algorithm, obtains the lowest complexity and achieves good throughput performance in single cell OFDMA system. However, in multi-cell multi-sector OFDMA networks, PR algorithm is not applicable because it does not take ICI into consideration. The proposed PIB algorithm balances the number of loading bits for the desired User Equipment (UE) and the major interfering UE, as well as optimizes the SINR performance; meanwhile, IBLA avoids loading certain number of interfering bits which would make SINR unqualified. Simulations confirm the ICI management effectiveness and feasibility of both the proposals.

Downlink Resource Allocation with Multi-Objective Optimization in OFDMA Systems

A downlink radio resource allocation algorithm is proposed for orthogonal frequency division multiple access( OFDMA) systems. The resource allocation problem about system throughput and user fairness is formulated based on the multi-objective optimization theory. Then the optimality conditions are derived,according to which a joint subcarrier and power allocation algorithm is proposed. The simulation results show that the proposed algorithm can dynamically achieve arbitrary levels of compromise between throughput and fairness by adjusting the weighting coefficient,outperforming some static algorithms. In comparison,the classic maximum rate algorithm( MRA),max-min algorithm and proportional fairness( PF) algorithm can only achieve tradeoff in a certain level and are all special cases of the proposed algorithm.

Study on Multi-enterprise Collaborative Resource Planning Based Process-oriented Decision Model

Aiming to share the information,knowledge and optimizing resource via collaborating with multiple external partners across their supply chains,the concept model and system framework of multi-enterprises collaborative resource planning (MECORP) are put forward.While there is Considerable pressure to improve the operation of MECORP system,their inherent complexity can make modelling a MECORP system a difficult task.Yet there could be considerable benefits in designing MECORP taking into account the operation of the system.In order to address the central research issue of developing of a methodology that can assist a manager in making decisions by modelling the operation of MECORP system.The methodology called process-oriented deci- sion model (PODM) is presented in the paper.This uses an abstracted network to model MECORP system.The MECORP system supported by PODM,can effective optimize the manifold resource,coordinate the relationship of multiple partners and assist deci- sion.Finally,an industry excample of MECORP system is described to illustrate the application of PODM.

On the Need to Integrate Traditional Chinese and Western Medicine, and Pool Research Resources

The Chinese Academy of Sci-ences (CAS) is implementing theknowledge innovation program(KIP) on a trial basis. In my opinion,our knowledge innovation targetsshould be first of all precise and,secondly, able to boost our work. Ispecialize in hematology and mo-lecular biology. Under the

A Multi-Agent Resource Selection Model in Manufacturing Grid Environment

A group of agents are intimately cooperated to set the assessment indices, establish the weight of each index in overall result of evaluation, collect the experts＇ scores given to each available resource, and the manufacturing resource whose overall assessment value is highest is taken as the optimal choice. Architecture of the proposed system is outlined and an example is offered to show the process of accomplishing the assessment.

Genetic Modeling of GIS-Based Cell Clusters and Its Application in Mineral Resources Prediction

This paper presents a synthetic analysis method for multi sourced g eo logical data from geographic information system (GIS). In the previous practices of mineral resources prediction, a usually adopted methodology has been sta tistical analysis of cells delimitated based on thoughts of random sampling. Tha t might lead to insufficient utilization of local spatial information, for a cel l is treated as a point without internal structure. We now take “cell clusters ”, i. e. , spatial associations of cells, as basic units of statistics, thus th e spatial configuration information of geological variables is easier to be dete cted and utilized, and the accuracy and reliability of prediction are improved. We build a linear multi discriminating model for the clusters via genetic algor ithm. Both the right judgment rates and the in class vs. between class distan ce ratios are considered to form the evolutional adaptive values of the populati on. An application of the method in gold mineral resources prediction in east Xi njiang, China is presented.

Resource allocation optimization of equipment development task based on MOPSO algorithm

Resource allocation for an equipment development task is a complex process owing to the inherent characteristics,such as large amounts of input resources,numerous sub-tasks,complex network structures,and high degrees of uncertainty.This paper presents an investigation into the influence of resource allocation on the duration and cost of sub-tasks.Mathematical models are constructed for the relationships of the resource allocation quantity with the duration and cost of the sub-tasks.By considering the uncertainties,such as fluctuations in the sub-task duration and cost,rework iterations,and random overlaps,the tasks are simulated for various resource allocation schemes.The shortest duration and the minimum cost of the development task are first formulated as the objective function.Based on a multi-objective particle swarm optimization(MOPSO)algorithm,a multi-objective evolutionary algorithm is constructed to optimize the resource allocation scheme for the development task.Finally,an uninhabited aerial vehicle(UAV)is considered as an example of a development task to test the algorithm,and the optimization results of this method are compared with those based on non-dominated sorting genetic algorithm-II(NSGA-II),non-dominated sorting differential evolution(NSDE)and strength pareto evolutionary algorithm-II(SPEA-II).The proposed method is verified for its scientific approach and effectiveness.The case study shows that the optimization of the resource allocation can greatly aid in shortening the duration of the development task and reducing its cost effectively.

Relative Efficiency Evaluation on Water Resource Utilization

Water resource allocation was defined as an input-output question in this paper, and a preliminary input-output index system was set up. Then GEM （group eigenvalue method）-MAUE （multi-attribute utility theory） model was applied to evaluate relative efficiency of water resource allocation plans. This model determined weights of indicators by GEM, and assessed the allocation schemes by MAUE. Compared with DEA （Data Envelopment Analysis） or ANN （Artificial Neural Networks）, the mode was more applicable in some cases where decision-makers had preference for certain indicators