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Multi Objective Particle Swarm Optimization Based Cooperative Agents with Automated Negotiation [chapter]

Najwa Kouka, Raja Fdhila, Adel M. Alimi
2017 Lecture Notes in Computer Science  
This paper investigates a new hybridization of multi-objective particle swarm optimization (MOPSO) and cooperative agents (MOPSO-CA) to handle the problem of stagnation encounters in MOPSO, which leads  ...  Furthermore, we investigate the automated negotiation within agents in order to share the best knowledge. To validate our approach, several benchmarks are performed.  ...  Introduction to Multi Objective Particle Swarm Optimization PSO is a population-based search algorithm introduced by Kennedy and Eberhart [17] .  ... 
doi:10.1007/978-3-319-70093-9_28 fatcat:pwz2wpnvpnbgnotcn7t43fybci

Matchmaking in Multi-attribute Auctions using a Genetic Algorithm and a Particle Swarm Approach [chapter]

Simone A. Ludwig, Thomas Schoene
2011 Studies in Computational Intelligence  
The proposed approaches are based on a Genetic Algorithm (GA) and a Particle Swarm Optimization (PSO) approach to match buyers with sellers based on five attributes as closely as possible.  ...  This paper investigates multi-attribute auctions, and in particular the matchmaking of multiple buyers and sellers based on five attributes.  ...  Matchmaking in Multi-attribute Auctions using a Genetic Algorithm and a Particle Swarm Approach 17  ... 
doi:10.1007/978-3-642-24696-8_5 fatcat:gpbnr2y76rbi7n6b4i5xtaus7q

Multi-agent based manufacturing: current trends and challenges

Terrin Pulikottil, Luis Alberto Estrada-Jimenez, Hamood Ur Rehman, Jose Barata, Sanaz Nikghadam-Hojjati, Leszek Zarzycki
2021 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )  
This article, ends with an integrated discussion of emerging agent-based industrial challenges, a general conclusion and final remarks.  ...  In this regard, the current work surveys recent multi-agent based manufacturing approaches and provides a general vision of current trends focusing on frameworks/architectures, complementary technologies  ...  [11] : Negotiation of Manufacturing enterprise supply chain Multi-objective negotiation model, negotiating tactics and steps between purchasing agent and supplier agent Negotiation model and tactics  ... 
doi:10.1109/etfa45728.2021.9613555 fatcat:wdhgqjg4q5crbemdfdgf5yoyfy

Multi-agent evolutionary design of Beta fuzzy systems

Y. Jarraya, S. Bouaziz, Adel M. Alimi, A. Abraham
2014 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)  
The Methodology consists of two processes, a learning process using a clustering technique for the automated design of an initial Beta fuzzy system, and a multi-agent tuning process based on Particle Swarm  ...  Optimization algorithm to deal with the optimization of membership functions parameters and rule base.  ...  We attempt to develop an intelligent decision-making model based on multiple cooperative and negotiator agents to obtain the desired optimized fuzzy modeling system.  ... 
doi:10.1109/fuzz-ieee.2014.6891722 dblp:conf/fuzzIEEE/JarrayaBAA14 fatcat:ilbrklhhjvhbpk4picay4eo4jy

Flexible Workshop Scheduling Optimization Based On Multi-agent Technology

Jiang Xuesong, Tao Sun, Tao Qiaoyun, Jian Wang
2016 International Journal of Hybrid Information Technology  
Considering the complexity of flexible workshop scheduling, combined with plant production process characteristics and constraints, we constructed a multi-agent system model to solve multi-objective flexible  ...  Finally, this paper proved the validity of methods to solve the multi-objective flexible workshop scheduling optimization problems with examples on JADE platform.  ...  Quanyong Ju [6] proposed a multi-population particle swarm hybrid algorithm with tendentious search to improve search efficiency and quality, combining the advantages of multi-swarm particle swarm search  ... 
doi:10.14257/ijhit.2016.9.5.25 fatcat:onbehq7mpbdxxejcxdoe345fhi

Computational Intelligence Based Complex Adaptive System-of-System Architecture Evolution Strategy [chapter]

Siddhartha Agarwal, Cihan H. Dagli, Louis E. Pape
2015 Complex Systems Design & Management  
To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior.  ...  The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective.  ...  Binary Particle Swarm Optimization. In the original particle swarm optimization (PSO) the solutions are represented as a swarm of particles moving through the search space.  ... 
doi:10.1007/978-3-319-26109-6_9 dblp:conf/csdm/AgarwalDP15 fatcat:j3uqb2unfzgl3dsk46d7xjsctu

Scheduling multi–mode resource–constrained tasks of automated guided vehicles with an improved particle swarm optimization algorithm

Xiangjie Xiao, Yaohui Pan, Lingling Lv, Yanjun Shi
2021 IET Collaborative Intelligent Manufacturing  
Scheduling multi-mode resource-constrained tasks of automated guided vehicles with an improved particle swarm optimization algorithm. IET Collab. Intell.  ...  A modified particle swarm optimization (PSO) approach is presented for the multi-mode resource-constrained scheduling problem of automated guided vehicle (AGV) tasks.  ...  Each agent in the model is autonomous and has the ability to cooperate and negotiate with the other agents in the system.  ... 
doi:10.1049/cim2.12016 fatcat:vblta3pjlzahfa5aahrzm5opmy

From Automation to Autonomy - a New Trend for Smart Manufacturing [chapter]

H. S. Park
2013 DAAAM International Scientific Book 2013  
In order to guarantee the requested product quality and reduce downtime, the smart manufacturing (SM) which is considered as a new trend helps to meet objectives associated with these problems and improve  ...  For this purpose, in this article the benefits and challenges of self-optimizing manufacturing concept regarding its capability and responsibility are presented describing the adaptation to changing manufacturing  ...  In which, swarm intelligence technology is expressed either as evolutionary algorithms (ant colony optimization, particle swarm intelligence) (Anghinolfi, et al., 2007) or as a multi-agent system (Leitao  ... 
doi:10.2507/daaam.scibook.2013.03 fatcat:gbtgnr7rkbgrjcd5pzcycvdoty

Agent-based distributed manufacturing scheduling: an ontological approach

Salman Saeidlou, Mozafar Saadat, Ebrahim Amini Sharifi, Guiovanni D. Jules, Tao Peng
2019 Cogent Engineering  
The proposed agent-based approach was adapted from the bio-inspired metaheuristic-particle swarm optimisation (PSO), where agents move towards the schedule with the best global makespan.  ...  The multi-agent platform is built upon the Java Agent Development Environment (JADE) framework. The operation research case studies were used as benchmarks for the evaluation of the proposed model.  ...  The multi-agent system will be a system that is comprised of agents who are autonomous entities with the ability to cooperate with each other in order to fulfil a common goal.  ... 
doi:10.1080/23311916.2019.1565630 fatcat:5wd257ygyjfdppzaw4uuwlaj6i

Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review

Ioannis Antonopoulos, Valentin Robu, Benoit Couraud, Desen Kirli, Sonam Norbu, Aristides Kiprakis, David Flynn, Sergio Elizondo-Gonzalez, Steve Wattam
2020 Renewable & Sustainable Energy Reviews  
In automated negotiations related to energy DR, a buyer agent (consumer or aggregator) will negotiate with a seller agent (producer or retailer) on several issues, for all the periods of the day.  ...  As automated negotiations are performed by software agents, it is natural to use AI techniques to improve the negotiation strategy of the agents.  ...  [235] 2012 Multi-agent mechanism design Cooperatives' formation for DSM. 149 Haring et al.  ... 
doi:10.1016/j.rser.2020.109899 fatcat:wgpj4awq35dfzdq7ugumtrvo7q

Multi Agent Based Power Distribution System Restoration—A Literature Survey

Sarinda Lahiru Jayasinghe, Kullappu Thantrige Manjula Udayanga Hemapala
2015 Energy and Power Engineering  
Multi agent system (MAS) is one of the most dominant research wings which consist of several agents who interact with each other to achieve a common objective.  ...  This paper presents a complete literature review on available architectures for power distribution restoration and future trends in MAS based power system restoration.  ...  Genetic Algorithm (GA) & Particle Swarm Optimization From the literature it can be found new directions towards GA to be used in MAS [3] [82] [83] .  ... 
doi:10.4236/epe.2015.712052 fatcat:7qhxqdgnvrf4do42pdol2zvh24

MOANOFS: Multi-Objective Automated Negotiation based Online Feature Selection System for Big Data Classification [article]

Fatma BenSaid, Adel M. Alimi
2019 arXiv   pre-print
The proposed OFS system called MOANOFS (Multi-Objective Automated Negotiation based Online Feature Selection) uses two levels of decision.  ...  Index Terms: Feature selection, online learning, multi-objective automated negotiation, trust, classification, big data.  ...  To resolve such problem, we propose to integrate a multiobjective particle swarm optimization MOPSO in each agent-learner.  ... 
arXiv:1810.04903v2 fatcat:cyao7yssvbaqlji7ugxnytl6re

Intelligent Mobile Olfaction of Swarm Robots

Siti Nurmaini, Bambang Tutuko, Aulia Rahman Thoharsin
2013 IAES International Journal of Robotics and Automation  
This work presents intelligent mobile olfaction design and experimental results of intelligent swarm robots to detection a gas/odour source in an indoor environment by using multi agent based on hybrid  ...  Simple form of cooperation between Interval Type-2 Fuzzy Logic and Particle Swarm Optimization (IT2FL-PSO) algorithm is implemented in the olfaction strategies.  ...  For that purpose various approaches might be developed based on extremum seeking, gradient or hill climbing, multi-objective optimization algorithms, game theoretic strategies, negotiation based algorithms  ... 
doi:10.11591/ijra.v2i4.5085 fatcat:p4xxyex5nrhfnlf6db3h6ck4yq

Survey on artificial intelligence algorithms used in industrial robotics

Rabab Benotsmane, László Dudás, György Kovács
2020 Multidiszciplináris Tudományok  
In the second part of the study we will introduce the most important AI algorithms used to optimize and improve the trajectory of robotic arms.  ...  Multi-agent learning Coordination and negotiation are the essential keys of multi-agent learning, that combine machine learning-based agents which can be presented as robots, that are able to adapt to  ...  Particle Swarm Optimization Particle Swarm Optimization (PSO) is a stochastic optimization technique based on the intelligence and movement of birds swarms [29] .  ... 
doi:10.35925/j.multi.2020.4.23 fatcat:mdk2xuhigrgpdewkvizgncb5ve

Swarm Theory Applied To Air Traffic Flow Management

Sergio Torres
2012 Procedia Computer Science  
Combinatorial optimization techniques to solve the multi-objective traffic flow optimization problem are not practical; the vast number of variables and the exceedingly large Pareto front associated with  ...  This paper presents a different approach to TFM, inspired in swarm theory, that converts pilots into goal seeking agents that individually find local solutions to the optimization problem and as a whole  ...  One such algorithm, Particle Swarm Optimization (PSO), emulates swarm behavior to probe the solution space of an objective function and efficiently find the location where the optimal solution resides  ... 
doi:10.1016/j.procs.2012.09.105 fatcat:kp6gaby3mzckjphc73zssqieui
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