Multi-Start and Strategic Oscillation Methods — Principles to Exploit Adaptive Memory

2000 ◽  
pp. 1-23 ◽  
Author(s):  
Fred Glover
Keyword(s):  
Adaptive Memory ◽  
Strategic Oscillation

Adaptive memory in a directed forgetting task

2009 ◽  
Author(s):  
Kris Gunawan ◽  
David E. Copeland
Keyword(s):  
Directed Forgetting ◽  
Adaptive Memory

Adaptive Memory: Enhanced Location Memory After Survival Processing

2011 ◽  
Author(s):  
James S. Nairne ◽  
Joshua E. Vanarsdall ◽  
Josefa N. S. Pandeirada ◽  
Janell R. Blunt
Keyword(s):  
Adaptive Memory ◽  
Survival Processing ◽  
Location Memory

Adaptive memory: Is the animacy effect on memory due to richness of encoding?

2020 ◽  
Vol 46 (3) ◽  
pp. 416-426 ◽  
Author(s):  
Martin J. Meinhardt ◽  
Raoul Bell ◽  
Axel Buchner ◽  
Jan P. Röer
Keyword(s):  
Adaptive Memory

Explanation and Understanding in Animal Narratives

2018 ◽  
Author(s):  
David Herman
Keyword(s):  
Mental State ◽  
Paradigm Shifts ◽  
Top Down ◽  
Bottom Up ◽  
Human Behaviors ◽  
Discourse Practices ◽  
Strategic Oscillation ◽  
Experimental Narrative ◽  
The Way

With chapter 6 having described the way norms for mental-state ascriptions operate in a top-down manner in discourse domains, chapter 7 explores how individual narratives can in turn have a bottom-up impact on the ascriptive norms circulating within particular domains. To this end, the chapter discusses how Thalia Field’s 2010 experimental narrative Bird Lovers, Backyard employs a strategic oscillation between two nomenclatures that can be used to profile nonhuman as well as human behaviors: (1) the register of action, which characterizes behavior in terms of motivations, goals, and projects; and (2) the register of events, which characterizes behavior in terms of caused movements that have duration in time and direction in space. In braiding together these two registers, Field’s text suggests not only how discourse practices can be repatterned, but also how such repatterning enables broader paradigm shifts—in this case shifts in ways of understanding cross-species encounters and entanglements.

scholarly journals An Adaptive Memory Multi-Batch L-BFGS Algorithm for Neural Network Training

2020 ◽  
Vol 53 (2) ◽  
pp. 8199-8204
Author(s):  
Federico Zocco ◽  
Seán McLoone
Keyword(s):  
Neural Network ◽  
Adaptive Memory ◽  
Neural Network Training ◽  
Network Training

scholarly journals A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications

2021 ◽  
Vol 2021 (5) ◽  
Author(s):  
Csaba Balázs ◽  
◽  
Melissa van Beekveld ◽  
Sascha Caron ◽  
Barry M. Dillon ◽  
...  
Keyword(s):  
Random Sampling ◽  
Detailed Comparison ◽  
Global Optimisation ◽  
Adaptive Memory ◽  
Test Functions ◽  
Bee Colony ◽  
Covariance Matrix Adaptation ◽  
Global Fit ◽  
Adaptation Evolution ◽  
Optimisation Algorithms

Abstract Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms.

scholarly journals A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 853
Author(s):  
Jesús Sánchez-Oro ◽  
Ana D. López-Sánchez ◽  
Anna Martínez-Gavara ◽  
Alfredo G. Hernández-Díaz ◽  
Abraham Duarte
Keyword(s):  
Location Problem ◽  
State Of The Art ◽  
Path Relinking ◽  
Multiobjective Evolutionary Algorithms ◽  
Demand Point ◽  
High Quality ◽  
Nondominated Solutions ◽  
Center Location ◽  
Strategic Oscillation ◽  
N Demand

This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms.

An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries

2010 ◽  
Vol 202 (2) ◽  
pp. 401-411 ◽  
Author(s):  
Emmanouil E. Zachariadis ◽  
Christos D. Tarantilis ◽  
Chris T. Kiranoudis
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Adaptive Memory ◽  
Routing Problem

Adaptive memory: Is survival processing special?

2008 ◽  
Vol 59 (3) ◽  
pp. 377-385 ◽  
Author(s):  
James S. Nairne ◽  
Josefa N.S. Pandeirada
Keyword(s):  
Adaptive Memory ◽  
Survival Processing
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