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Long Path Problems
 Proceedings of the 3 rd Conference on Parallel Problems Solving from Nature
, 1994
"... . We demonstrate the interesting, counterintuitive result that simple paths to the global optimum can be so long that climbing the path is intractable. This means that a unimodal search space, which consists of a single hill and in which each point in the space is on a simple path to the global opt ..."
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optimum, can be difficult for a hillclimber to optimize. Various types of hillclimbing algorithms will make constant progress toward the global optimum on such long path problems. They will continuously improve their best found solutions, and be guaranteed to reach the global optimum. Yet we cannot wait
Biobjective Multiple and Long Path Problems
, 2012
"... HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
On the Effect of Connectedness for Biobjective Multiple and Long Path Problems
, 2012
"... Abstract. Recently, the property of connectedness has been claimed to give a strong motivation on the design of local search techniques for multiobjective combinatorial optimization. Indeed, when connectedness holds, a basic Pareto local search, initialized with at least one nondominated solution, ..."
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of efficient solutions. In this paper, we propose the biobjective long and multiple path problems. We show experimentally that, on the first problem, even if the efficient set is connected, a local search may be outperformed by a simple evolutionary algorithm in the sampling of the efficient set
Long Path Problems for MutationBased Algorithms
, 1992
"... Introduction In this note we present a class of problems designed to be difficult for randomized search procedures that exploit local search space information. In particular, these problems challenge hillclimbers and mutation algorithms. The problems are difficult not because they contain local opt ..."
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Cited by 1 (0 self)
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the only "path" up the hill to the global optimum is very long and narrow. The length of the path grows exponentially with the size of the (binary) problem, l. Constructing hard problems for a class of algorithms is part of a recognized methodology for analyzing, understanding, and bounding
How Mutation and Selection Solve Long Path Problems in Polynomial Expected Time
, 1996
"... It is shown by means of Markov chain analysis that unimodal binary long path problems can be solved by mutation and elitist selection in a polynomially bounded number of trials on average. 1 Unimodality of Binary Functions The notion of unimodal functions usually appears in the theory of optimizati ..."
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Cited by 55 (2 self)
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It is shown by means of Markov chain analysis that unimodal binary long path problems can be solved by mutation and elitist selection in a polynomially bounded number of trials on average. 1 Unimodality of Binary Functions The notion of unimodal functions usually appears in the theory
Research Note: Long Path Problems for MutationBased Algorithms
"... Introduction In this note we present a class of problems designed to be difficult for randomized search procedures that exploit local search space information. In particular, these problems challenge hillclimbers and mutation algorithms. The problems are difficult not because they contain local opt ..."
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the only "path" up the hill to the global optimum is very long and narrow. The length of the path grows exponentially with the size of the (binary) problem, l. Constructing hard problems for a class of algorithms is part of a recognized methodology for analyzing, understanding, and bounding
A HighThroughput Path Metric for MultiHop Wireless Routing
, 2003
"... This paper presents the expected transmission count metric (ETX), which finds highthroughput paths on multihop wireless networks. ETX minimizes the expected total number of packet transmissions (including retransmissions) required to successfully deliver a packet to the ultimate destination. The E ..."
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Cited by 1078 (5 self)
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This paper presents the expected transmission count metric (ETX), which finds highthroughput paths on multihop wireless networks. ETX minimizes the expected total number of packet transmissions (including retransmissions) required to successfully deliver a packet to the ultimate destination
Probabilistic Roadmaps for Path Planning in HighDimensional Configuration Spaces
 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION
, 1996
"... A new motion planning method for robots in static workspaces is presented. This method proceeds in two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collisionfree configurations and whose edg ..."
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Cited by 1276 (124 self)
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edges correspond to feasible paths between these configurations. These paths are computed using a simple and fast local planner. In the query phase, any given start and goal configurations of the robot are connected to two nodes of the roadmap; the roadmap is then searched for a path joining these two
Regularization paths for generalized linear models via coordinate descent
, 2009
"... We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, twoclass logistic regression, and multinomial regression problems while the penalties include ℓ1 (the lasso), ℓ2 (ridge regression) and mixtures of the two (the elastic ..."
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Cited by 698 (14 self)
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elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.
Cognitive load during problem solving: effects on learning
 COGNITIVE SCIENCE
, 1988
"... Considerable evidence indicates that domain specific knowledge in the form of schemes is the primary factor distinguishing experts from novices in problemsolving skill. Evidence that conventional problemsolving activity is not effective in schema acquisition is also accumulating. It is suggested t ..."
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Cited by 603 (13 self)
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Considerable evidence indicates that domain specific knowledge in the form of schemes is the primary factor distinguishing experts from novices in problemsolving skill. Evidence that conventional problemsolving activity is not effective in schema acquisition is also accumulating. It is suggested
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