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Spillover algorithm: A decentralised coordination approach for multi-robot production planning in open shared factories

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2021年 70卷 102110-102110页

作者： Lujak, Marin Fernandez, Alberto Onaindia, Eva Univ Lille CERI Numer IMT Lille Douai F-59000 Lille France Univ Rey Juan Carlos Madrid 28933 Spain Univ Politecn Valencia Valencian Res Inst AI Valencia 46022 Spain

Open and shared manufacturing factories typically dispose of a limited number of industrial robots and/or other production resources that should be properly allocated to tasks in time for an effective and efficient system performance. In particular, we deal with the dynamic capacitated production planning problem with sequence independent setup costs where quantities of products to manufacture need to be determined at consecutive periods within a given time horizon and products can be anticipated or back-ordered related to the demand period. We consider a decentralised multi-agent variant of this problem in an open factory setting with multiple owners of robots as well as different owners of the items to be produced, both considered self-interested and individually rational. Existing solution approaches to the classic constrained lot-sizing problem are centralised exact methods that require sharing of global knowledge of all the participants' private and sensitive information and are not applicable in the described multi-agent context. Therefore, we propose a computationally efficient decentralised approach based on the spillover effect that solves this NP-hard problem by distributing decisions in an intrinsically decentralised multi-agent system environment while protecting private and sensitive information. To the best of our knowledge, this is the first decentralised algorithm for the solution of the studied problem in intrinsically decentralised environments where production resources and/or products are owned by multiple stakeholders with possibly conflicting objectives. To show its efficiency, the performance of the Spillover algorithm is benchmarked against state-of-the-art commercial solver CPLEX 12.8.

关键词： Capacitated production planning Multi-robot systems Multi-agent coordination decentralised algorithm Shared factories

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decentralised optimal vehicle-to-grid coordination with forecast errors

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第7期13卷 989-996页

作者： Zou, Suli Ma, Zhongjing Yang, Nan Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

Considering vehicle-to-grid (V2G) coordination schemes, plug-in electric vehicles (PEVs) are expected to be an energy storage system (ESS) to smooth out the fluctuation of the intermittent renewable energy source (RES) and the power load profile. In this study, firstly the optimal coordination of PEVs minimising total costs is shown to possess the valley-fill and peak-shift property for any pair of adjacent instants. Due to the decoupling relationship among the admissible sets of coordination behaviours of all the PEVs in the modelling issue, a decentralised algorithm is proposed by applying the gradient projection method, such that the coordination behaviours of individual PEVs can be updated locally and simultaneously. It is proved that the convergence and optimality of the proposed method are guaranteed in case the step-size parameter of the update procedure is in a certain region, and its performance does not rely on the shape of the net demand trajectory. Furthermore, a receding horizon-based algorithm is presented to account for the forecast errors occurred in the predictions of PEV populations, RES productions and inelastic load profiles. The results developed in this study are demonstrated with numerical simulations and comparisons with other decentralised methods are also provided.

关键词： minimisation electric vehicles smart power grids energy storage gradient methods step-size parameter receding horizon-based algorithm forecast errors PEV populations RES productions inelastic load profiles decentralised methods electric vehicles energy storage system intermittent renewable energy source power load profile optimal coordination peak-shift property decoupling relationship admissible sets decentralised algorithm gradient projection method decentralised optimal vehicle-to-grid coordination schemes plug-in electric vehicles cost minimization valley-fill property coordination behaviours net demand trajectory numerical simulations

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decentralised hierarchical coordination of electric vehicles in multi-microgrid systems

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第13期13卷 2899-2906页

作者： Zou, Suli Ma, Zhongjing Yang, Nan BIT Natl Key Lab Complex Syst Intelligent Control & D Sch Automat Beijing 100081 Peoples R China China Elect Power Res Inst Beijing 100192 Peoples R China

Here, the authors study the optimal coordination of electric vehicles (EVs) in a multi-microgrid (MMG) system with respect to a given time-of-use (TOU) price trajectory over a multi-time period. The authors firstly formulate a class of EV charging/discharging coordination problems for each individual microgrid (MG) to minimise the electricity cost of this MG, while the implemented strategy may result in high variations of the total demand and even build new peaky demands. To mitigate these negative effects, the authors build an aggregate optimisation problem with quadratic cost function under certain bounds on the electricity costs of each MG. The authors further propose a decentralised method for the underlying optimisation problem and verify the convergence of the system to the optimal strategy with a logarithmic convergence rate. Furthermore, the authors consider the power exchange capacity between the MMG system and the main grid, and present a decentralised algorithm to obtain an optimal strategy that minimises the system cost under this capacity constraint. Also, the convergence, the optimality, and the convergence rate of the proposed algorithm are shown.

关键词： distributed power generation minimisation electric vehicles pricing electricity cost MG total demand peaky demands aggregate optimisation problem quadratic cost function decentralised method logarithmic convergence rate MMG system decentralised algorithm optimality decentralised hierarchical coordination electric vehicles multimicrogrid system optimal coordination EVs multitime period coordination problems individual microgrid optimisation problem system cost minimization time-of-use price trajectory

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decentralised signal processing on graphs via matrix inverse approximation

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SIGNAL PROCESSING 2019年 165卷 292-302页

作者： Jiang, Junzheng Tay, David B. Guilin Univ Elect Technol Sch Informat & Commun Guilin 541004 Peoples R China Deakin Univ Sch Informat Technol Waurn Ponds Vic 3216 Australia

In the processing of signals defined over graph domains, it is highly desirable to have algorithms that can be implemented in a decentralised manner, whereby each node only needs to exchange information within a localized subgraph of nodes. The most common example is when the subgraph consist of immediate neighbors and this allows for distributed processing. Many graph signal operators, in their original forms, are not amenable to distributed processing. To overcome this deficiency, a polynomial approximation is usually applied to the original operator to yield a distributed operator which is a matrix polynomial of the graph shift matrix. This approach however is only applicable when the original operator is a function of the graph shift matrix. In this paper, we propose a generalized approach to approximate graph signal operators that are not necessary functions of the shift matrix. The key idea here is to restrict the approximated matrix inverse to have small geodesic-width so that multiplication with the small geodesic-width matrix can be implemented in a decentralised manner. Furthermore, to increase the accuracy of the approximated operator, an iterative algorithm which also has the decentralised property and low computational complexity, is proposed. We apply the proposed approach to signal inpainting and signal reconstruction in filter banks. Numerical results verify the effectiveness of the proposed algorithm. The proposed algorithms can also be used to efficiently solve linear system of equations. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Graph signal processing Matrix inverse approximation decentralised algorithm Graph shift matrix

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Stackelberg game-based decentralised supply chain coordination considering both futures and spot markets

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INTERNATIONAL JOURNAL OF CONTROL 2020年第12期93卷 2804-2813页

作者： Zou, Suli Ma, Zhongjing Wang, Peng Liu, Xiangdong ETH Swiss Fed Inst Technol Dept Informat Technol & Elect Engn Automat Control Lab Zurich Switzerland Beijing Inst Technol BIT Sch Automat Beijing Peoples R China Natl Key Lab Complex Syst Intelligent Control & D Beijing Peoples R China

As generators and retailers can trade energy through either forward contracts or a pool in the electricity markets, we propose a hierarchical structure to capture the supply chain decision-making processes taking into account the interaction between the futures and spot markets. At each level, we model the sequential acting of generators and retailers as a Stackelberg game where generators behave as leaders and retailers behave as followers to maximise their individual payoff. Generators and retailers make decisions of the energy quantity in the spot market in the lower level with respect to the contracts signed in the futures market, while they determine contracts in the upper level with respect to the latest information from the spot market. After verifying the existence of the hierarchical equilibrium, we develop a decentralised algorithm to implement the equilibrium with only local information available for both generators and retailers. In the supply chain regime which incorporates both futures and spot markets, we show that it benefits the electricity market in reducing the pool price. The results are corroborated through numerical examples.

关键词： Supply chain futures markets spot markets Stackelberg game hierarchical equilibrium decentralised algorithm

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Dynamic virtual machine consolidation using a multi-agent system to optimise energy efficiency in cloud computing

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2020年 108卷 288-301页

作者： Mc Donnell, Nicola Howley, Enda Duggan, Jim Natl Univ Ireland Galway Sch Comp Sci Univ Rd Galway Ireland

Cloud computing has seen rapid growth in the last decade, as a result of this there is an increasing concern about the energy requirement of cloud data centres. One approach to tackle this issue is dynamic virtual machine consolidation (DVMC) where virtual machines (VMs) are packed into fewer hosts, while hosts which have no VMs are placed into a hibernate mode. DVMC is traditionally solved with strategies that build on centralised topologies. One disadvantage of these solutions is that they don' t scale well in very large data centres as the manager node becomes a bottleneck and a single point of failure. The nature of the problem lends itself to a decentralised solution which is preferred over a centralised one when a problem is: inherently modular, large in scale, in a very dynamic environment, and when communication channels can experience message delays and loss. We propose Gossip Contracts (GC), a new multi-agent framework for crafting decentralised co-operation strategies. GC is inspired by the Gossip and Contract Net protocols. Using GC we developed a GC-based DVMC strategy and compared it to two popular strategies: Sercon, a centralised strategy, and ecoCloud, a distributed strategy. One of the comparison experiments uses Google cluster-usage traces;a dataset of real usage data from a Google data centre. The GC-based strategy performs best with respect to SLA Violations, and is similar to or outperforms other strategies with respect to power consumption. By its decentralised nature, GC does not have a single point of failure. (C) 2020 Published by Elsevier B.V.

关键词： Cloud computing Energy efficiency Dynamic Virtual Machine Consolidation decentralised algorithm Contract Net Gossip

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Fully distributed AC power flow (ACPF) algorithm for distribution systems

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IET SMART GRID 2019年第2期2卷 155-162页

作者： Pourbabak, Hajir Ajao, Adetokunbo Chen, Tao Su, Wencong Univ Michigan Coll Engn & Comp Sci Dept Elect & Comp Engn Dearborn MI 48128 USA

Power flow is one of the basic tools for system operation and control. Due to its nature, which determines the complex nodal voltages, line flows, currents and losses, it enforces a large computation load on a power system. A distributed/decentralised algorithm unburdens the central controller and shares the total computation load with all agents. Therefore, such algorithms are an effective method for dealing with power flow complexity. In this study, a distributed method based on a linearised AC power system is proposed. First, the linearisation procedure of a comprehensive non-linear AC power flow (ACPF) is detailed. Second, a distributed method is presented based upon the linear ACPF equations. Three case studies are presented to evaluate the overall performance of the proposed method. In the first case study, the accuracy level of both linearised ACPF and distributed ACPF is assessed. In the second case study, the dynamic performance of distributed ACPF is investigated based on the load sudden changes. In the third case study, the scalability of the proposed distributed ACPF is evaluated by applying it to a larger power system.

关键词： load flow power system security power system management AC power flow algorithm distribution systems system operation control complex nodal voltages distributed decentralised algorithm central controller shares total computation load effective method power flow complexity distributed method linearised AC power system nonlinear AC power flow linear ACPF equations case study linearised ACPF distributed ACPF larger power system

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Evolved Gossip Contracts - A Framework for Designing Multi-agent Systems 16th

Evolved Gossip Contracts - A Framework for Designing Multi-a...

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16th International Conference on Parallel Problem Solving from Nature (PPSN)

作者： Mc Donnell, Nicola Howley, Enda Duggan, Jim Natl Univ Ireland Galway Galway Ireland

ISBN: (纸本)9783030581114;9783030581121

Multi-agent systems are systems of autonomous interacting agents acting in an environment to achieve a common goal. One of the most interesting aspects of multi-agent systems is when they exhibit emergence;where the whole is considered greater than the sum of the parts. Designing multi-agents systems is challenging, and doing this in an automated way has been described as "one of the holy grails of artificial intelligence and agent-based modelling". In previous research, we presented a novel decentralised cooperation protocol called Gossip Contracts (GC), which is inspired by Contract Net and Gossip Protocol. Here we present Evolved Gossip Contracts (EGC), a new framework which builds on GC and uses evolutionary computing to tailor GC to address a specific problem. We evaluate the EGC framework and the experimental results indicate that it is a promising approach for the automated design of decentralised strategies.

关键词： Multi-agent systems decentralised algorithm Genetic Programming

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