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multi-agent-optimization
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A multi-agent optimization formulation of earthquake disaster prevention and management
, Article European Journal of Operational Research ; Volume 229, Issue 1 , 2013 , Pages 261-275 ; 03772217 (ISSN) ; Poorzahedy, H ; Nassiri, H ; Nourinejad, M ; Sharif University of Technology
2013
Abstract
Natural earthquake disasters are unprecedented incidents which take many lives as a consequence and cause major damages to lifeline infrastructures. Various agencies in a country are responsible for reducing such adverse impacts within specific budgets. These responsibilities range from before to after the incident, targeting one of the main phases of disaster management (mitigation, preparedness, and response). Use of OR in disaster management and coordination of its phases has been mostly ignored and highly recommended in former reviews. This paper presents a formulation to coordinate three main agencies and proposes a heuristic approach to solve the different introduced sub-problems. The...
Agent-Based Optimization of Integrated Energy and Product Networks
, Ph.D. Dissertation Sharif University of Technology ; Bozorgmehry Boozarjomehry, Ramin (Supervisor) ; Pishvaie, Mahmoud Reza (Supervisor)
Abstract
The industrial paradigm shift toward intelligent and sustainable management stimulates policymakers to leverage artificial intelligence for the decentralized planning of chemical industries with energy networks. By doing so, this work firstly presents a simulation framework to investigate the rigorous transient behavior of integrated systems comprising natural gas and power transmission networks, along with a chemical plant whose feedstock is natural gas. This framework entails dynamic models for the gas transmission network and the SynGas plant, and a continuous-time AC-power flow formulation with dispatchable loads. It addresses the following key challenges: (i) analyzing energy and...
Application of a Multi-agent Optimization Model in Pre-disaster Planning with Consideration of Overall Loss: Case of Bam 2003 Earthquake
, M.Sc. Thesis Sharif University of Technology ; Poorzahedy, Hossain (Supervisor)
Abstract
Earthquake is one of the deadliest natural hazards that has taken more than 400 thousand lives, only in the last decade. Iran is one of the countries that are at high risk of potential death toll resulting from such hazards, firstly because it is located in a potentially high-risk zone, the so-called earthquake belt and, secondly because of its problems in the management of disastrous situations (especially, pre-disaster management). Bam 2003 earthquake is one of the most painful experiences in this context. So, in this research, emphasizing on the practical use of optimization models, an existing model is applied on the damaged area of the Bam earthquake. The mentioned model considers the...
Facility location optimization via multi-agent robotic systems
, Article 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC, Sanya, 6 April 2008 through 8 April 2008 ; 2008 , Pages 287-292 ; 9781424416851 (ISBN) ; Sayyaadi, H ; Sharif University of Technology
2008
Abstract
A facility location problem deals with locating the best place for a group of facilities, among distinct demand points, minimizing a certain locational optimization function. In this paper, distributed, asynchronous, and scalable algorithms are presented for solving a facility location problem known as continuous n-median problem (generalized Fermat-Weber problem) via multi-agent robotic systems. The algorithms are discussed both in continuous and discrete time domain, and their validity is proved. It is also shown that the solution of this facility location problem is the set of points that are the geometric medians of their corresponding Voronoi cells
Multi-agent machine learning in self-organizing systems
, Article Information Sciences ; Volume 581 , 2021 , Pages 194-214 ; 00200255 (ISSN) ; Sharif University of Technology
Elsevier Inc
2021
Abstract
This paper develops a novel insight and procedure that includes a variety of algorithms for finding the best solution in a structured multi-agent system with internal communications and a global purpose. In other words, it finds the optimal communication structure among agents and the optimal policy in this structure. First, a unique reinforcement learning algorithm is proposed to find the optimal policy of each agent in a fixed structure with non-linear function approximators like artificial neural networks (ANN) and with eligibility traces. Secondly, a mechanism is presented to perform self-organization based on the information of the learned policy. Finally, an algorithm that can discover...
Active leading through obstacles using ant-colony algorithm
, Article Neurocomputing ; Volume 88 , 2012 , Pages 67-77 ; 09252312 (ISSN) ; Etemadi, S ; Alasty, A ; Vossoughi, G. R ; Boroushaki, M ; Sharif University of Technology
Abstract
In presence of obstacles, inter-agent pulling actions must be bounded. In this case, to remain connected to the group, the leader-agent (LA) must perform an active leading strategy. In this paper, an active leading algorithm is proposed which monitors the neighborhood of the LA and adjusts its velocity. The algorithm is based on the ant colony optimization (ACO) technique. As a real time optimization package, the ACO algorithm maximizes influence of the LA on the group, leading to fast flocking. Comparison with another optimization method is provided as well. Simulations show that the algorithm is successful and cost effective