Papers Multiobjective Optimization
“Multiobjective Optimization” 태그가 달린 논문 155편 · 필터 해제
Multiobjective Optimization Training of PLDA for Speaker Verification
Most current state-of-the-art text-independent speaker verification systems take probabilistic linear discriminant analysis (PLDA) as their backend classifiers. The parameters of PLDA are often estimated by maximizing th…
Multiobjective OptimizationSpeaker VerificationText-Independent Speaker VerificationInferring Parameters Through Inverse Multiobjective Optimization
Given a set of human's decisions that are observed, inverse optimization has been developed and utilized to infer the underlying decision making problem. The majority of existing studies assumes that the decision making …
Decision MakingMultiobjective OptimizationIncorporating Deep Visual Features into Multiobjective based Multi-view Search Results Clustering
Current paper explores the use of multi-view learning for search result clustering. A web-snippet can be represented using multiple views. Apart from textual view cued by both the semantic and syntactic information, a co…
ClusteringImage CaptioningMultiobjective OptimizationMULTI-VIEW LEARNING+1Multiobjective Test Problems with Degenerate Pareto Fronts
In multiobjective optimisation, a set of scalable test problems with a variety of features allow researchers to investigate and evaluate the abilities of different optimisation algorithms, and thus can help them to desig…
Multiobjective OptimizationMultiobjective Optimization Differential Evolution Enhanced with Principle Component Analysis for Constrained Optimization
Multiobjective evolutionary algorithms (MOEAs) have been successfully applied to a number of constrained optimization problems. Many of them adopt mutation and crossover operators from differential evolution. However, th…
Evolutionary AlgorithmsMultiobjective OptimizationGlobal Convergence Analysis of the Flower Pollination Algorithm: A Discrete-Time Markov Chain Approach
Flower pollination algorithm is a recent metaheuristic algorithm for solving nonlinear global optimization problems. The algorithm has also been extended to solve multiobjective optimization with promising results. In th…
global-optimizationMultiobjective OptimizationThe Benefits of Population Diversity in Evolutionary Algorithms: A Survey of Rigorous Runtime Analyses
Population diversity is crucial in evolutionary algorithms to enable global exploration and to avoid poor performance due to premature convergence. This book chapter reviews runtime analyses that have shown benefits of p…
DiversityEvolutionary AlgorithmsMultiobjective OptimizationInterpretable Apprenticeship Learning with Temporal Logic Specifications
Recent work has addressed using formulas in linear temporal logic (LTL) as specifications for agents planning in Markov Decision Processes (MDPs). We consider the inverse problem: inferring an LTL specification from demo…
Multiobjective OptimizationPreselection via Classification: A Case Study on Evolutionary Multiobjective Optimization
In evolutionary algorithms, a preselection operator aims to select the promising offspring solutions from a candidate offspring set. It is usually based on the estimated or real objective values of the candidate offsprin…
ClassificationEvolutionary AlgorithmsGeneral ClassificationMultiobjective OptimizationProtein design by multiobjective optimization: evolutionary and non-evolutionary approaches
Traditional simulation-based protein design considers energy minimization of candidate conformations as a singleobjective combinatorial optimization problem. In this paper we consider a challenging protein design problem…
Combinatorial OptimizationEfficient ExplorationMultiobjective OptimizationProtein Design+1Evolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results
In this report, we suggest nine test problems for multi-task multi-objective optimization (MTMOO), each of which consists of two multiobjective optimization tasks that need to be solved simultaneously. The relationship b…
Multiobjective OptimizationDiscovering Evolutionary Stepping Stones through Behavior Domination
Behavior domination is proposed as a tool for understanding and harnessing the power of evolutionary systems to discover and exploit useful stepping stones. Novelty search has shown promise in overcoming deception by col…
DiversityMultiobjective OptimizationOptimization of distributions differences for classification
In this paper we introduce a new classification algorithm called Optimization of Distributions Differences (ODD). The algorithm aims to find a transformation from the feature space to a new space where the instances in t…
ClassificationGeneral ClassificationMultiobjective OptimizationDominance Move: A Measure of Comparing Solution Sets in Multiobjective Optimization
One of the most common approaches for multiobjective optimization is to generate a solution set that well approximates the whole Pareto-optimal frontier to facilitate the later decision-making process. However, how to ev…
Decision MakingMultiobjective OptimizationMultiobjective Optimization of Solar Powered Irrigation System with Fuzzy Type-2 Noise Modelling
Optimization is becoming a crucial element in industrial applications involving sustainable alternative energy systems. During the design of such systems, the engineer/decision maker would often encounter noise factors (…
Multiobjective OptimizationPlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization
Over the last three decades, a large number of evolutionary algorithms have been developed for solving multiobjective optimization problems. However, there lacks an up-to-date and comprehensive software platform for rese…
Evolutionary AlgorithmsMultiobjective OptimizationTransfer Learning based Dynamic Multiobjective Optimization Algorithms
One of the major distinguishing features of the dynamic multiobjective optimization problems (DMOPs) is the optimization objectives will change over time, thus tracking the varying Pareto-optimal front becomes a challeng…
BIG-bench Machine LearningMultiobjective OptimizationTransfer LearningSwarm Intelligence for Multiobjective Optimization of Extraction Process
Multi objective (MO) optimization is an emerging field which is increasingly being implemented in many industries globally. In this work, the MO optimization of the extraction process of bioactive compounds from the Gard…
Multiobjective OptimizationNon-Gaussian Random Generators in Bacteria Foraging Algorithm for Multiobjective Optimization
Random generators or stochastic engines are a key component in the structure of metaheuristic algorithms. This work investigates the effects of non-Gaussian stochastic engines on the performance of metaheuristics when so…
Multiobjective OptimizationSandUsing Well-Understood Single-Objective Functions in Multiobjective Black-Box Optimization Test Suites
Several test function suites are being used for numerical benchmarking of multiobjective optimization algorithms. While they have some desirable properties, like well-understood Pareto sets and Pareto fronts of various s…
BenchmarkingMultiobjective Optimization