scholarly journals Search Dynamics on Multimodal Multiobjective Problems

2019 ◽  
Vol 27 (4) ◽  
pp. 577-609 ◽  
Author(s):  
P. Kerschke ◽  
H. Wang ◽  
M. Preuss ◽  
C. Grimme ◽  
A. H. Deutz ◽  
...  
Keyword(s):  
Multiobjective Optimization ◽  
Local Search ◽  
Objective Functions ◽  
Test Bed ◽  
Decision Space ◽  
Multiobjective Problems ◽  
Definition Of ◽  
Visualization Techniques ◽  
Single Objective ◽  
Selection Of

We continue recent work on the definition of multimodality in multiobjective optimization (MO) and the introduction of a test bed for multimodal MO problems. This goes beyond well-known diversity maintenance approaches but instead focuses on the landscape topology induced by the objective functions. More general multimodal MO problems are considered by allowing ellipsoid contours for single-objective subproblems. An experimental analysis compares two MO algorithms, one that explicitly relies on hypervolume gradient approximation, and one that is based on local search, both on a selection of generated example problems. We do not focus on performance but on the interaction induced by the problems and algorithms, which can be described by means of specific characteristics explicitly designed for the multimodal MO setting. Furthermore, we widen the scope of our analysis by additionally applying visualization techniques in the decision space. This strengthens and extends the foundations for Exploratory Landscape Analysis (ELA) in MO.

scholarly journals A NNIA Scheme for Timetabling Problems

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Yu Lei ◽  
Jiao Shi
Keyword(s):  
Multiobjective Optimization ◽  
Local Search ◽  
Pareto Front ◽  
Optimization Problem ◽  
Solution Space ◽  
Crossover Operator ◽  
Number Of Solutions ◽  
Examination Timetabling ◽  
Optimization Operator ◽  
Single Objective

This paper presents a memetic multiobjective optimization algorithm based on NNIA for examination timetabling problems. In this paper, the examination timetabling problem is considered as a two-objective optimization problem while it is modeled as a single-objective optimization problem generally. Within the NNIA framework, the special crossover operator is utilized to search in the solution space; two local search techniques are employed to optimize these two objectives and a diversity-keeping strategy which consists of an elitism group operator and an extension optimization operator to ensure a sufficient number of solutions in the pareto front. The proposed algorithm was tested on the most widely used uncapacitated Carter benchmarks. Experimental results prove that the proposed algorithm is a competitive algorithm.

scholarly journals Combining the cross-entropy algorithm and ∈-constraint method for multiobjective optimization

2021 ◽  
Vol 7 (2) ◽  
pp. 299-311
Author(s):  
Abdelmajid Ezzine ◽  
Abdellah Alla ◽  
Nadia Raissi
Keyword(s):  
Multiobjective Optimization ◽  
Local Search ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Cross Entropy ◽  
Multiobjective Optimization Problem ◽  
Cross Entropy Method ◽  
The Cross ◽  
Constraint Method ◽  
Single Objective

Abstract This paper aims to propose a new hybrid approach for solving multiobjective optimization problems. This approach is based on a combination of global and local search procedures. The cross-entropy method is used as a stochastic model-based method to solve the multiobjective optimization problem and reach a first elite set of global solutions. In the local search step, an ∈-constraint method converts the multiobjective optimization problem to a series of parameterized single-objective optimization problems. Then, sequential quadratic programming (SQP) is used to solve the derived single-objective optimization problems allowing to reinforce and improve the global results. Numerical examples are used to demonstrate the efficiency and effectiveness of the proposed approach.

scholarly journals Adaptive dropout for high-dimensional expensive multiobjective optimization

2021 ◽  
Author(s):  
Jianqing Lin ◽  
Cheng He ◽  
Ran Cheng
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
State Of The Art ◽  
High Dimensional ◽  
Benchmark Problems ◽  
Decision Space ◽  
Decision Variables ◽  
Training Samples ◽  
Multiobjective Optimization Problems ◽  
Selection Of

AbstractVarious works have been proposed to solve expensive multiobjective optimization problems (EMOPs) using surrogate-assisted evolutionary algorithms (SAEAs) in recent decades. However, most existing methods focus on EMOPs with less than 30 decision variables, since a large number of training samples are required to build an accurate surrogate model for high-dimensional EMOPs, which is unrealistic for expensive multiobjective optimization. To address this issue, we propose an SAEA with an adaptive dropout mechanism. Specifically, this mechanism takes advantage of the statistical differences between different solution sets in the decision space to guide the selection of some crucial decision variables. A new infill criterion is then proposed to optimize the selected decision variables with the assistance of surrogate models. Moreover, the optimized decision variables are extended to new full-length solutions, and then the new candidate solutions are evaluated using expensive functions to update the archive. The proposed algorithm is tested on different benchmark problems with up to 200 decision variables compared to some state-of-the-art SAEAs. The experimental results have demonstrated the promising performance and computational efficiency of the proposed algorithm in high-dimensional expensive multiobjective optimization.

Selection and Preparation of Specific Tissue Regions For Tem Using Large Epoxy-Embedded Blocks

1973 ◽  
Vol 31 ◽  
pp. 324-325 ◽  
Author(s):  
P. M. Lowrie ◽  
W. S. Tyler
Keyword(s):  
Electron Microscopy ◽  
Anatomical Structures ◽  
Ultrastructural Studies ◽  
Transmission Electron ◽  
Microscopic Evaluation ◽  
Embedded Blocks ◽  
Specific Tissue ◽  
Definition Of ◽  
Areas Of Interest ◽  
Selection Of

The importance of examining stained 1 to 2μ plastic sections by light microscopy has long been recognized, both for increased definition of many histologic features and for selection of specimen samples to be used in ultrastructural studies. Selection of specimens with specific orien ation relative to anatomical structures becomes of critical importance in ultrastructural investigations of organs such as the lung. The uantity of blocks necessary to locate special areas of interest by random sampling is large, however, and the method is lacking in precision. Several methods have been described for selection of specific areas for electron microscopy using light microscopic evaluation of paraffin, epoxy-infiltrated, or epoxy-embedded large blocks from which thick sections were cut. Selected areas from these thick sections were subsequently removed and re-embedded or attached to blank precasted blocks and resectioned for transmission electron microscopy (TEM).

scholarly journals Promotion of Resilience in Migrants: A Systematic Review of Study and Psychosocial Intervention

2021 ◽  
Author(s):  
Maria Ciaramella ◽  
Nadia Monacelli ◽  
Livia Concetta Eugenia Cocimano
Keyword(s):  
Systematic Review ◽  
Psychosocial Intervention ◽  
Life Experiences ◽  
Psychosocial Interventions ◽  
Migrant Population ◽  
Methodological Choices ◽  
Research Questions ◽  
Definition Of ◽  
Selection Of

AbstractThis systematic review aimed to contribute to a better and more focused understanding of the link between the concept of resilience and psychosocial interventions in the migrant population. The research questions concerned the type of population involved, definition of resilience, methodological choices and which intervention programmes were targeted at migrants. In the 90 articles included, an heterogeneity in defining resilience or not well specified definition resulted. Different migratory experiences were not adequately considered in the selection of participants. Few resilience interventions on migrants were resulted. A lack of procedure’s descriptions that keep in account specific migrants’ life-experiences and efficacy’s measures were highlighted.

scholarly journals Getting to Hope: Perspectives from Patients and Caregivers Living with Chronic Childhood Illness

Children ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 525
Author(s):  
Emily von Scheven ◽  
Bhupinder K. Nahal ◽  
Rosa Kelekian ◽  
Christina Frenzel ◽  
Victoria Vanderpoel ◽  
...  
Keyword(s):  
Conceptual Model ◽  
Research Question ◽  
Young Patients ◽  
Future Research ◽  
Childhood Onset ◽  
Virtual Focus Groups ◽  
Definition Of ◽  
Selection Of ◽  
Chronic Childhood ◽  
Research Studies

Promoting hope was identified in our prior work as the top priority research question among patients and caregivers with diverse childhood-onset chronic conditions. Here, we aimed to construct a conceptual model to guide future research studies of interventions to improve hope. We conducted eight monthly virtual focus groups and one virtual workshop with patients, caregivers, and researchers to explore key constructs to inform the model. Discussions were facilitated by Patient Co-Investigators. Participants developed a definition of hope and identified promotors and inhibitors that influence the experience of hope. We utilized qualitative methods to analyze findings and organize the promotors and inhibitors of hope within three strata of the socio-ecologic framework: structural, interpersonal, and intrapersonal. Participants identified three types of interventions to promote hope: resources, navigation, and activities to promote social connection. The hope conceptual model can be used to inform the selection of interventions to assess in future research studies aimed at improving hope and the specification of outcome measures to include in hope research studies. Inclusion of the health care system in the model provides direction for identifying strategies for improving the system and places responsibility on the system to do better to promote hope among young patients with chronic illness and their caregivers.

scholarly journals Examining and Fine-tuning the Selection of Glycan Compositions with GlyConnect Compozitor

2020 ◽  
Vol 19 (10) ◽  
pp. 1602-1618 ◽  
Author(s):  
Thibault Robin ◽  
Julien Mariethoz ◽  
Frédérique Lisacek
Keyword(s):  
Search Engine ◽  
Posttranslational Modifications ◽  
Search Engines ◽  
Web Application ◽  
Contextual Information ◽  
Fine Tuning ◽  
Data Sources ◽  
Web Interface ◽  
Definition Of ◽  
Selection Of

A key point in achieving accurate intact glycopeptide identification is the definition of the glycan composition file that is used to match experimental with theoretical masses by a glycoproteomics search engine. At present, these files are mainly built from searching the literature and/or querying data sources focused on posttranslational modifications. Most glycoproteomics search engines include a default composition file that is readily used when processing MS data. We introduce here a glycan composition visualizing and comparative tool associated with the GlyConnect database and called GlyConnect Compozitor. It offers a web interface through which the database can be queried to bring out contextual information relative to a set of glycan compositions. The tool takes advantage of compositions being related to one another through shared monosaccharide counts and outputs interactive graphs summarizing information searched in the database. These results provide a guide for selecting or deselecting compositions in a file in order to reflect the context of a study as closely as possible. They also confirm the consistency of a set of compositions based on the content of the GlyConnect database. As part of the tool collection of the Glycomics@ExPASy initiative, Compozitor is hosted at https://glyconnect.expasy.org/compozitor/ where it can be run as a web application. It is also directly accessible from the GlyConnect database.

General Schema Theory for Genetic Programming with Subtree-Swapping Crossover: Part II

2003 ◽  
Vol 11 (2) ◽  
pp. 169-206 ◽  
Author(s):  
Riccardo Poli ◽  
Nicholas Freitag McPhee
Keyword(s):  
Genetic Programming ◽  
Schema Theory ◽  
Exact Formulation ◽  
Expected Number ◽  
Size Evolution ◽  
General Schema ◽  
Definition Of ◽  
Effective Fitness ◽  
Selection Of ◽  
Exact Definition

This paper is the second part of a two-part paper which introduces a general schema theory for genetic programming (GP) with subtree-swapping crossover (Part I (Poli and McPhee, 2003)). Like other recent GP schema theory results, the theory gives an exact formulation (rather than a lower bound) for the expected number of instances of a schema at the next generation. The theory is based on a Cartesian node reference system, introduced in Part I, and on the notion of a variable-arity hyperschema, introduced here, which generalises previous definitions of a schema. The theory includes two main theorems describing the propagation of GP schemata: a microscopic and a macroscopic schema theorem. The microscopic version is applicable to crossover operators which replace a subtree in one parent with a subtree from the other parent to produce the offspring. Therefore, this theorem is applicable to Koza's GP crossover with and without uniform selection of the crossover points, as well as one-point crossover, size-fair crossover, strongly-typed GP crossover, context-preserving crossover and many others. The macroscopic version is applicable to crossover operators in which the probability of selecting any two crossover points in the parents depends only on the parents' size and shape. In the paper we provide examples, we show how the theory can be specialised to specific crossover operators and we illustrate how it can be used to derive other general results. These include an exact definition of effective fitness and a size-evolution equation for GP with subtree-swapping crossover.

Development of a Stepped Calibration Approach for XAJ Hydrological Model

2013 ◽  
Vol 405-408 ◽  
pp. 2222-2225
Author(s):  
Qian Li ◽  
Wei Min Bao ◽  
Jing Lin Qian
Keyword(s):  
Root Mean Square Error ◽  
Objective Function ◽  
Traditional Method ◽  
Hydrological Model ◽  
Model Performance ◽  
Layer By Layer ◽  
Mean Square ◽  
Objective Functions ◽  
Single Objective ◽  
Calibration Approach

This paper discusses the conceptual stepped calibration approach (SCA) which has been developed for the Xinanjiang (XAJ) model. Multi-layer and multi-objective functions which can make optimization work simpler and more effective are introduced in this procedure. In all eight parameters were considered, they were divided into four layers according to the structure of XAJ model, and then calibrated layer by layer. The SCA procedure tends to improve the performance of the traditional method of calibration (thus, using a single objective function, such as root mean square error RMSE). The compared results demonstrate that the SCA yield better model performance than RMSE.

A new representation for a robot grasping quality measure

Robotica ◽  
1995 ◽  
Vol 13 (3) ◽  
pp. 287-295 ◽  
Author(s):  
Venugopal K. Varma ◽  
Uri Tasch
Keyword(s):  
Objective Function ◽  
Material Properties ◽  
Graphical Representation ◽  
Contact Forces ◽  
Geometric Constraints ◽  
Objective Functions ◽  
Finger Force ◽  
Finger Forces ◽  
Robot Grasping ◽  
Selection Of

SummaryWhen an object is held by a multi-fingered hand, the values of the contact forces can be multivalued. An objective function, when used in conjunction with the frictional and geometric constraints of the grasp, can however, give a unique set of finger force values. The selection of the objective function in determining the finger forces is dependent on the type of grasp required, the material properties of the object, and the limitations of the röbot fingers. In this paper several optimization functions are studied and their merits highlighted. The paper introduces a graphical representation of the finger force values and the objective functions that enable one to select and compare various grasping configurations. The impending motion of the object at different torque and finger force values are determined by observing the normalized coefficient of friction plots.

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