5,011 research outputs found
Compelled to do the right thing
We use a model of opinion formation to study the consequences of some
mechanisms attempting to enforce the right behaviour in a society. We start
from a model where the possible choices are not equivalent (such is the case
when the agents decide to comply or not with a law) and where an imitation
mechanism allow the agents to change their behaviour based on the influence of
a group of partners. In addition, we consider the existence of two social
constraints: a) an external authority, called monitor, that imposes the correct
behaviour with infinite persuasion and b) an educated group of agents that act
upon their fellows but never change their own opinion, i.e., they exhibit
infinite adamancy. We determine the minimum number of monitors to induce an
effective change in the behaviour of the social group, and the size of the
educated group that produces the same effect. Also, we compare the results for
the cases of random social interactions and agents placed on a network. We have
verified that a small number of monitors are enough to change the behaviour of
the society. This also happens with a relatively small educated group in the
case of random interactions.Comment: 8 pages, 9 figures, submitted to EPJ
A simplex-like search method for bi-objective optimization
We describe a new algorithm for bi-objective optimization, similar to the Nelder Mead simplex
algorithm, widely used for single objective optimization. For diferentiable bi-objective functions on
a continuous search space, internal Pareto optima occur where the two gradient vectors point in
opposite directions. So such optima may be located by minimizing the cosine of the angle between
these vectors. This requires a complex rather than a simplex, so we term the technique the \cosine
seeking complex". An extra beneft of this approach is that a successful search identifes the direction
of the effcient curve of Pareto points, expediting further searches. Results are presented for some
standard test functions. The method presented is quite complicated and space considerations here
preclude complete details. We hope to publish a fuller description in another place
Scheduling aircraft landings - the static case
This is the publisher version of the article, obtained from the link below.In this paper, we consider the problem of scheduling aircraft (plane) landings at an airport. This problem is one of deciding a landing time for each plane such that each plane lands within a predetermined time window and that separation criteria between the landing of a plane and the landing of all successive planes are respected. We present a mixed-integer zero–one formulation of the problem for the single runway case and extend it to the multiple runway case. We strengthen the linear programming relaxations of these formulations by introducing additional constraints. Throughout, we discuss how our formulations can be used to model a number of issues (choice of objective function, precedence restrictions, restricting the number of landings in a given time period, runway workload balancing) commonly encountered in practice. The problem is solved optimally using linear programming-based tree search. We also present an effective heuristic algorithm for the problem. Computational results for both the heuristic and the optimal algorithm are presented for a number of test problems involving up to 50 planes and four runways.J.E.Beasley. would like to acknowledge the financial support of the Commonwealth Scientific and Industrial Research Organization, Australia
Multi-objective engineering shape optimization using differential evolution interfaced to the Nimrod/O tool
This paper presents an enhancement of the Nimrod/O optimization tool by interfacing DEMO, an external multiobjective optimization algorithm. DEMO is a variant of differential evolution – an algorithm that has attained much popularity in the research community, and this work represents the first time that true multiobjective optimizations have been performed with Nimrod/O. A modification to the DEMO code enables multiple objectives to be evaluated concurrently. With Nimrod/O’s support for parallelism, this can reduce the wall-clock time significantly for compute intensive objective function evaluations. We describe the usage and implementation of the interface and present two optimizations. The first is a two objective mathematical function in which the Pareto front is successfully found after only 30 generations. The second test case is the three-objective shape optimization of a rib-reinforced wall bracket using the Finite Element software, Code_Aster. The interfacing of the already successful packages of Nimrod/O and DEMO yields a solution that we believe can benefit a wide community, both industrial and academic
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