20 research outputs found

    Analysis of profit of generation company in power market

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    In recent decades, the operation of power systems in the power market model has been researched and applied by many countries. The profit of generation companies is always interested in research to ensure operation and balance of power market. This paper studies and analysis profit of generation companies to participate in the power market. In addition, this paper has analyzed the participation of new generation in the power market with 39-bus IEEE power system

    Approches de rĂ©solution de problĂšmes d’ordonnancement multi-agent Ă  machines parallĂšles identiques

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    We are studying ”non-disjoint multi-agent scheduling problems‘. These models consider different agents associated with non-disjoint subsets of jobs, each of them aims to minimize an objective function that depends only on its own jobs. Two types of criteria are con- sidered: minimization of the makespan and minimization of the number of late jobs. We are therefore looking for the best compromise solution between the agents. These prob- lems constitute particular class of ”multi-agent“ scheduling problems that have developed considerably due to their interests in scheduling and combinatorial optimization domains. In our work, we focused on problems with identical parallel machines. In a first part, we study the case of a single machine, then the case where the jobs are equal length. Thus, polynomial scheduling problems are identified. In a second part, we address the identical parallel machine scheduling problems with two agents. Our study focuses on the enumer- ation of the Pareto front by the Δ-constraint approach using mathematical mixed integer programming. The computational results show the limitations of these methods. To solve large instances, greedy heuristics, hybrid heuristics, metaheuristic or even matheuristic are developed. The computational results show their performance compared to exact methods or to the proposed lower bound.Nous Ă©tudions des « problĂšmes d’ordonnancement multiagent non-disjoint ». Ces mod- Ăšles considĂšrent diffĂ©rents agents associĂ©s Ă  des sous-ensembles de travaux non nĂ©cessaire- ment disjoints, chacun d’eux vise Ă  minimiser un objectif qui ne dĂ©pend que de ses propres travaux. Deux types de critĂšres sont considĂ©rĂ©s : minimisation du makespan et du nom- bre de travaux en retard. Nous cherchons donc les meilleurs compromis entre les critĂšres des agents. Ces problĂšmes sont une classe particuliĂšre des problĂšmes d’ordonnancement « multi-agents » qui ont connu une grande expansion par leurs intĂ©rĂȘts dans le domaine de l’ordonnancement et l’optimisation combinatoire. Dans nos travaux, nous nous sommes intĂ©ressĂ©s aux problĂšmes Ă  machines parallĂšles identiques. Dans une premiĂšre partie, nous Ă©tudions le cas d’une seule machine et celui oĂč les travaux ont des durĂ©es identiques. Ainsi, des problĂšmes polynomiaux sont identifiĂ©s. Dans une seconde partie de nos travaux, nous abordons le problĂšme Ă  machines parallĂšles identiques avec deux agents. Notre Ă©tude porte sur l’énumĂ©ration du front de Pareto par l’approche Δ-contrainte en utilisant des modĂšles mathĂ©matiques Ă  variables mixtes. Les rĂ©sultats des expĂ©rimentations montrent les limites de ces mĂ©thodes. Pour rĂ©soudre des problĂšmes de grande taille, des heuristiques glou- tonnes, hybrides, des mĂ©taheuristiques ou encore une matheuristique sont dĂ©veloppĂ©es. Des expĂ©rimentations sont menĂ©es afin de montrer leurs performances par rapport aux mĂ©thodes exactes ou par rapport Ă  la borne infĂ©rieure proposĂ©e

    Approches de rĂ©solution de problĂšmes d’ordonnancement multi-agent Ă  machines parallĂšles identiques

    No full text
    We are studying ”non-disjoint multi-agent scheduling problems‘. These models consider different agents associated with non-disjoint subsets of jobs, each of them aims to minimize an objective function that depends only on its own jobs. Two types of criteria are con- sidered: minimization of the makespan and minimization of the number of late jobs. We are therefore looking for the best compromise solution between the agents. These prob- lems constitute particular class of ”multi-agent“ scheduling problems that have developed considerably due to their interests in scheduling and combinatorial optimization domains. In our work, we focused on problems with identical parallel machines. In a first part, we study the case of a single machine, then the case where the jobs are equal length. Thus, polynomial scheduling problems are identified. In a second part, we address the identical parallel machine scheduling problems with two agents. Our study focuses on the enumer- ation of the Pareto front by the Δ-constraint approach using mathematical mixed integer programming. The computational results show the limitations of these methods. To solve large instances, greedy heuristics, hybrid heuristics, metaheuristic or even matheuristic are developed. The computational results show their performance compared to exact methods or to the proposed lower bound.Nous Ă©tudions des « problĂšmes d’ordonnancement multiagent non-disjoint ». Ces mod- Ăšles considĂšrent diffĂ©rents agents associĂ©s Ă  des sous-ensembles de travaux non nĂ©cessaire- ment disjoints, chacun d’eux vise Ă  minimiser un objectif qui ne dĂ©pend que de ses propres travaux. Deux types de critĂšres sont considĂ©rĂ©s : minimisation du makespan et du nom- bre de travaux en retard. Nous cherchons donc les meilleurs compromis entre les critĂšres des agents. Ces problĂšmes sont une classe particuliĂšre des problĂšmes d’ordonnancement « multi-agents » qui ont connu une grande expansion par leurs intĂ©rĂȘts dans le domaine de l’ordonnancement et l’optimisation combinatoire. Dans nos travaux, nous nous sommes intĂ©ressĂ©s aux problĂšmes Ă  machines parallĂšles identiques. Dans une premiĂšre partie, nous Ă©tudions le cas d’une seule machine et celui oĂč les travaux ont des durĂ©es identiques. Ainsi, des problĂšmes polynomiaux sont identifiĂ©s. Dans une seconde partie de nos travaux, nous abordons le problĂšme Ă  machines parallĂšles identiques avec deux agents. Notre Ă©tude porte sur l’énumĂ©ration du front de Pareto par l’approche Δ-contrainte en utilisant des modĂšles mathĂ©matiques Ă  variables mixtes. Les rĂ©sultats des expĂ©rimentations montrent les limites de ces mĂ©thodes. Pour rĂ©soudre des problĂšmes de grande taille, des heuristiques glou- tonnes, hybrides, des mĂ©taheuristiques ou encore une matheuristique sont dĂ©veloppĂ©es. Des expĂ©rimentations sont menĂ©es afin de montrer leurs performances par rapport aux mĂ©thodes exactes ou par rapport Ă  la borne infĂ©rieure proposĂ©e

    Ordonnancement de travaux interférants avec la date d'achÚvement et contraint nombre de retards des travaux

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    International audiencePour illustrer notre approche, considĂ©rons le cas d’un seul agent local et un agent global. Le problĂšmeestnotĂ©1|IN,d(G),d(1)|CGmax,PU1 i .Nous pouvons dĂ©duire les rĂ©sultats suivants sous condition que chaque travail en commun entre les les agents a une seule date de ïŹn souhaitĂ©e commune

    Minimisation de la date d'achĂšvement et du nombre de travaux en retard pour l'ordonnancement multiagent

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    International audienceLes problĂšmes d’ordonnancement sont des problĂšmes d’optimisation combinatoire. Il s’agit de trouver une meilleure politique pour l’organisation et la rĂ©alisation des activitĂ©s ou des travaux dans le temps en leur allouant les ressources nĂ©cessaires (consommables ou renouvelables) et en respectant leur(s) contraintes d’exĂ©cution. Ces problĂšmes se rencontrent dans tout systĂšme de production de bien ou de service. Dans cette Ă©tude, deux types de fonctions objectif sont considĂ©rĂ©s : minimisation de la date d’achĂšvement globale (Cmax) et la minimisation du nombre de travaux en retard (Sum Uj). Pour calculer une solution de Pareto, nous utilisons l’approche Δ-contrainte

    Minimisation de la date d'achĂšvement et du nombre de travaux en retard pour l'ordonnancement multiagent non-disjoint

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    International audienceNotre dĂ©marche est illustrĂ©e au cas de deux agents (K = 2). Nous montrons comment certains rĂ©sultats peuvent (ou pas) se gĂ©nĂ©raliser aux cas d’un nombre K quelconque d’agents. Selon la notation des problĂšmes d’ordonnancement multiagent introduite dans [1], le problĂšme Ă©tudiĂ© est notĂ© : P 2|ND, dB, SumUj≀ Q |CmaxA, oĂč ND indique que les ensembles des travaux sont non-disjoints. Quand l’approche Δ-contrainte est considĂ©rĂ©e. Dans ce dernier cas, le problĂšme consiste Ă  trouver un ordonnancement minimisant l’objectif de l’agent A tout en conservant la valeur de l’objectif de l’agent B infĂ©rieure Ă  un seuil donnĂ© Q.

    Non-disjoint Multi-agent Scheduling Problem on Identical Parallel Processors

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    International audienceScheduling problems in which agents (users, customers, application masters, resource manager, etc.) have to share the same set(s) of resources are at the frontier of combinatorial optimization and cooperative game theory. This paper deals with scheduling problems arising when two agents, each with a set of nonpreemptive jobs, compete to perform their respective jobs on two common identical parallel machines. Each agent aims at minimizing a certain objective function that depends on the completion times of its jobs only. The objective functions we consider in our study are makespan and number of tardy jobs. The agents may share some jobs and this problem is called non-disjoint multi-agent scheduling problem [3]. Finding the optimal solution for one agent with a constraint on the other agent's cost function is known to be N P-hard. To obtain best compromise solutions for each agent, we propose polynomial and pseudo-polynomial heuristics. Two mixed integer linear programming models are developed to calculate exact non-dominated solutions. Experimental results are conducted to measure the solutions quality given by heuristics

    Phytoplankton community composition variation under natural and prolonged saline intrusion simulations

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    This study assessed phytoplankton community composition variation under two discrete salinity intrusion rate experiments. Experiment 1 simulated salinization under short-term, natural tidally induced rates of salinity change typical of the Mekong Delta, Vietnam (0–30‰ in 6 h), while Experiment 2 simulated salinization under a longer, more gradual rate of salinity change (0–30‰ at 5‰ increase per week). Phytoplankton community composition was, overall, more abundant following prolonged salinity change (Experiment 2) than rapid, tidally-induced salinity change (Experiment 1). Under both experimental conditions phytoplankton species number and density varied with changes in salinity, indicating a strong effect of salinity regardless of its rate of change. At the end of the salinity acclimation, Cyanobacteria, Chlorophyta, Euglenophyta and Bacillariophyta were all most abundant at a salinity of 5‰ after a short-term tidally simulated change in salinity, but with a longer, more gradual change in salinity, the abundance of different groups varied with salinity; With a longer, more gradual change in salinity, Chlorophyta was most abundant at 5–10‰ salinity, while Cyanobacteria, Euglenophyta and Bacillariophyta were all most abundant at a salinity of 5‰. The species composition in treatments of less than 10‰ had high similarity with the freshwater environment while treatments of 30‰ (Experiment 1) and 25‰ (Experiment 2) had high similarity with the natural seawater environment. This study demonstrates the utility of mesocosm experiments for understanding phytoplankton community composition variation in natural aquatic ecosystems under rapid and prolonged saline intrusion rates and predicting associated impacts on food webs in natural water bodies and aquaculture systems.This study demonstrates the possibility to simulate salinity changes in the mesocosm systems for understanding and predicting phytoplankton community composition variation in natural aquatic ecosystems under rapid and prolonged saline intrusion rates which associate with potential impacts on food webs as well as aquaculture systems

    Electronic Transport in the V-Shaped Edge Distorted Zigzag Graphene Nanoribbons with Substitutional Doping

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    Density-functional theory (DFT) in combination with the nonequilibrium Green’s function formalism is used to study the effect of substitutional doping on the electronic transport properties of V-shaped edge distorted zigzag graphene nanoribbons (DZGNRs), in which DZGNRs with the various widths of four-, six-, and eight-zigzag chains are passivated by H atoms. In this work, Si atoms are used to substitute carbon atoms located at the center of the samples. Our calculated results have determined that Si can change the material type by the number of dopants. We found that the transmission spectrum strongly depends on the various widths. The width of eight-zigzag chains exhibits the largest transmission among four- and six-zigzag chains, and the single Si substitution presents larger transmission than the double case. The obtained results are explained in terms of electron localization in the system due to the presence of distortion at edge and impurities. The relationships between the transmission spectrum, the device density of states, and the I-V curves indicate that DZGNRs are the highly potential material for electronic nanodevices
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