12,559 research outputs found
Multiagent cooperation for solving global optimization problems: an extendible framework with example cooperation strategies
This paper proposes the use of multiagent cooperation for solving global optimization problems through the introduction of a new multiagent environment, MANGO. The strength of the environment lays in itsflexible structure based on communicating software agents that attempt to solve a problem cooperatively. This structure allows the execution of a wide range of global optimization algorithms described as a set of interacting operations. At one extreme, MANGO welcomes an individual non-cooperating agent, which is basically the traditional way of solving a global optimization problem. At the other extreme, autonomous agents existing in the environment cooperate as they see fit during run time. We explain the development and communication tools provided in the environment as well as examples of agent realizations and cooperation scenarios. We also show how the multiagent structure is more effective than having a single nonlinear optimization algorithm with randomly selected initial points
Resource inventory for fostering industrial symbiosis practices
In this paper, we investigate the potential environmental benefits obtainable in Industrial Symbiotic Networks (ISNs) in case firms stock wastes when the demand is lower than supply. We design multiagent-based simulations to model the spontaneous emergence and operations of ISNs over time where firms are involved in substitution-based symbiotic relationships. In each simulation, we compute: 1) the amount of resources saved with respect to the amount of produced wastes; and 2) the amount of resources not saved because of the lack of inventory compared to the produced amounts. Results show that waste stocking could be a useful strategy to reduce the negative effects of the waste market dynamicity on the match between demand and suppl
Bounded Distributed Flocking Control of Nonholonomic Mobile Robots
There have been numerous studies on the problem of flocking control for
multiagent systems whose simplified models are presented in terms of point-mass
elements. Meanwhile, full dynamic models pose some challenging problems in
addressing the flocking control problem of mobile robots due to their
nonholonomic dynamic properties. Taking practical constraints into
consideration, we propose a novel approach to distributed flocking control of
nonholonomic mobile robots by bounded feedback. The flocking control objectives
consist of velocity consensus, collision avoidance, and cohesion maintenance
among mobile robots. A flocking control protocol which is based on the
information of neighbor mobile robots is constructed. The theoretical analysis
is conducted with the help of a Lyapunov-like function and graph theory.
Simulation results are shown to demonstrate the efficacy of the proposed
distributed flocking control scheme
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