scholarly journals Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Tomás de Jesús Mateo Sanguino ◽  
Jhon Carlos Mendoza Betancourt
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Wireless Lans ◽  
Evolutionary Strategy ◽  
Problem Solving Skills ◽  
Critical Design ◽  
Simultaneous Design ◽  
Multiobjective Approach ◽  
Optimal Deployment ◽  
Optimal Modeling

Communication infrastructure planning is a critical design task that typically requires handling complex concepts on networking aimed at optimizing performance and resources, thus demanding high analytical and problem-solving skills to engineers. To reduce this gap, this paper describes an optimization algorithm—based on evolutionary strategy—created as an aid for decision-making prior to the real deployment of wireless LANs. The developed algorithm allows automating the design process, traditionally handmade by network technicians, in order to save time and cost by improving the WLAN arrangement. To this end, we implemented a multiobjective genetic algorithm (MOGA) with the purpose of meeting two simultaneous design objectives, namely, to minimize the number of APs while maximizing the coverage signal over a whole planning area. Such approach provides efficient and scalable solutions closer to the best network design, so that we integrated the developed algorithm into an engineering tool with the goal of modelling the behavior of WLANs in ICT infrastructures. Called WiFiSim, it allows the investigation of various complex issues concerning the design of IEEE 802.11-based WLANs, thereby facilitating design of the study and design and optimal deployment of wireless LANs through complete modelling software. As a result, we comparatively evaluated three target applications considering small, medium, and large scenarios with a previous approach developed, a monoobjective genetic algorithm.

Towards Academic Successor Selection Modelling with Genetic Algorithm in Multi-Criteria Problems

2018 ◽  
Vol 7 (4.33) ◽  
pp. 130
Author(s):  
Atiqa Zukreena Zakuan ◽  
Shuzlina Abdul-Rahman ◽  
Hamidah Jantan ◽  
. .
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Succession Planning ◽  
Fitness Function ◽  
Academic Staff ◽  
Fitness Value ◽  
Selection Decision ◽  
The University ◽  
Hierarchy Process

Succession planning is a subset of talent management that deals with multi-criteria and uncertainties which are quite complicated, ambiguous, fuzzy and troublesome. Besides that, the successor selection involves the process of searching the best candidate for a successor for an optimal selection decision. In an academic scenario, the quality of academic staff contributes to achieving goals and improving the performance of the university at the international level. The process of selecting appropriate academic staff requires good criteria in decision-making. The best candidate's position and criteria for the selection of academic staff is the responsibility of the Human Resource Management (HRM) to select the most suitable candidate for the required position. The various criteria that are involved in selecting academic staff includes research publication, teaching skills, personality, reputation and financial performance. Previously, most studies on multi-criteria decision-making adopt Fuzzy Analytical Hierarchy Process (FAHP). However, this method is more complex because it involved many steps and formula and may not produce the optimum results. Therefore, Genetic Algorithm (GA) is proposed in this research to address this problem in which a fitness function for the successor selection is based on the highest fitness value of each chromosome.    

scholarly journals inPractice: a practical nursing package for clinical decisions

2005 ◽  
Vol 13 (1) ◽  
Author(s):  
Barry Ip ◽  
Annlouise Cavanna ◽  
Beverley Corbett
Keyword(s):  
Decision Making ◽  
Nursing Students ◽  
Health Science ◽  
Computer Assisted ◽  
Practical Nursing ◽  
Learning Program ◽  
Close Collaboration ◽  
Problem Solving Skills ◽  
Key Points ◽  
The University

This paper examines the recent development of a computer-assisted learning program—in Practice— at the School of Health Science, in the University of Wales Swansea. The project, which began in 2001, was developed in close collaboration with The Meningitis Trust, the aim being to produce a software package to increase nursing students’ knowledge of meningitis-related illnesses, and to enhance their decision-making and problem-solving skills by using lifelike scenarios. It incorporates two multimedia meningitis modules incorporating the use of text, film, and sound, in which students are presented with information about the illness (symptoms, treatment etc.), and are required to use their knowledge to make decisions at various key points. A general discussion of decision-making theories and CAL design principles is presented, which has provided a foundation for the main design aspects of the package. This is followed by an outline of how the program was created to promote students’ application of knowledge and their decision-making and problemsolving skills. Results from an evaluation questionnaire are presented. Consideration is also given as to how the program can be extended.DOI: 10.1080/0968776042000339808

scholarly journals Creating private criteria for A-CDM effectiveness to take into account the interests of decision-making participants in a dynamic environment

2020 ◽  
Vol 23 (6) ◽  
pp. 53-64
Author(s):  
G. N. Lebedev ◽  
V. B. Malygin
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Production Process ◽  
Action Plan ◽  
Dynamic Environment ◽  
Weather Conditions ◽  
Collaborative Decision Making ◽  
Emergency Situations ◽  
Dynamic Priorities ◽  
Collaborative Decision

We consider the problem of collaborative decision making of the production process at airlines (CDM) in dynamically changing conditions of occurrence of emergency situations that make changes in the action plan. In the production process, due to the different orientation of the tasks to be solved, the solution may require a large or small number of possible variant solutions. The article presents a concrete example of such a situation affecting the conventional three services of the aviation complex, each with its own interests in the overall production process. The solution to this problem is the only option in favor of the overall production process. For this purpose, several designations and assumptions have been introduced, the list of which can be supplemented. Dynamic priorities are defined for each participant of the process. Optimization of collaborative decision-making can be achieved either by a simple search for solutions, or by using a genetic algorithm that allows you to get a suboptimal solution that meets the requirements of the participants in the process using a smaller number of iterations in real time. In this example, we consider a situation that occurs in a real enterprise due to bad weather conditions. Thus, dynamic priorities are assigned based on a multiplicative form for delayed flights, considering the interests of participants in the process, private criteria are formed for ranking flights at each step of rescheduling, and a genetic algorithm is applied. As a result, we obtained four solutions to the disruption caused by external factors. The first three options correspond to the interests of three parties concerned, and the fourth one is consolidated. All the solutions were different, which indicates the need for an objective and reasonable decision-making apparatus for joint management of the production process. The proposed mathematical apparatus has this ability and prospects for implementation.

scholarly journals The Effectiveness of Leadership Skills Development Program for University Students / Üniversite Öğrencilerine Yönelik Liderlik Becerileri Geliştirme Programının Etkililiği

2017 ◽  
Vol 6 (3) ◽  
pp. 65 ◽  
Author(s):  
Ramazan Cansoy
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Goal Setting ◽  
Communication Skills ◽  
Education Program ◽  
Leadership Skills ◽  
Emotional Awareness ◽  
Problem Solving Skills ◽  
Skills Group ◽  
Skills Education

<p><strong>Abstract</strong></p><p>The aim of this study was to examine the effectiveness of a leadership skills education program for higher education students. In this program, education was provided to improve the desire for struggle and goal setting, communication skills, group skills, problem-solving skills, decision-making skills, responsibility awareness, trusting and trustworthiness awareness, leadership awareness and emotional awareness within the framework of leadership skills. The study group of the research consists of final-year students with the average age of 23.8 years studying at the Faculty of Economics of Karabük University in the 2016-2017 academic year.  The data of the study were collected with the “Youth leadership characteristics scale”, “Emotional self-awareness scale” and “Awareness of leader and leadership scale”.  The retrospective pretest-posttest experimental model was used in the study.  The differentiation levels of the pretest and posttest scores of the students included in the education program were examined with the Wilcoxon signed-rank test. It was observed at the end of the study that the desire for struggle and goal setting, communication skills, group skills, problem-solving skills, decision-making skills, responsibility awareness, trusting and trustworthiness awareness, leadership awareness and emotional awareness levels of the students who participated in the education program significantly increased from a moderately sufficient level to a quite sufficient level. It was indicated that the applied leadership skills education program was effective.</p><p><strong>Öz</strong></p><p>Bu araştırmanın amacı, yükseköğretim öğrencilerine dönük olarak geliştirilen bir liderlik becerileri eğitimi programının etkililiğinin incelenmesidir. Bu programda liderlik becerileri çerçevesinde mücadele isteği ve hedef koyma, iletişim becerileri, grup becerileri, problem çözme becerileri, karar verme becerileri, sorumluluk farkındalığı, güven duyma ve güvenilir olma farkındalığı, liderlik farkındalığı ve duygusal farkındalığı geliştirmeye yönelik bir eğitim verilmiştir. Araştırmanın çalışma grubunu 2016-2017 yılında Karabük Üniversitesi’ndeki ortalama yaşı 23.8 olan iktisat fakültesi son sınıf öğrencileri oluşturmaktadır. Araştırmanın verileri “Gençlik Liderlik Özellikleri Ölçeği”, “Duygusal Benlik Bilinci Ölçeği” ve “Lider ve Liderlik Hakkinda Farkindalik Ölçeği” ile toplanmıştır. Çalışmada geçmişe dayalı öntest-son test deneysel modeli kullanılmıştır.  Eğitim programında yer alan öğrencilerin öntest ve sontest puanlarının farklılaşma düzeyleri Wilcoxon işaretli sıralar testi ile sınanmıştır. Araştırma sonunda eğitim programına katılan öğrencilerde mücadele isteği ve hedef koyma, iletişim becerileri, grup becerileri, problem çözme becerileri, karar verme becerileri, sorumluluk farkındalığı, güven duyma ve güvenilir olma farkındalığı, liderlik farkındalığı ve duygusal farkındalık düzeylerinin orta derecede yeterli düzeyden   oldukça yeterli düzeye  anlamlı bir şekilde yükseldiği görülmüştür. Uygulanan liderlik becerileri eğitimi programının etkili olduğu ortaya konulmuştur.</p>

Modeling Knowledge Employee’s Turnover Based on P-SVM

2010 ◽  
Vol 121-122 ◽  
pp. 825-831
Author(s):  
Yong Zhao ◽  
Ye Zheng Liu
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Model Development ◽  
Forecast Model ◽  
Support Vector ◽  
Multi Criteria Decision Making ◽  
Parameters Selection ◽  
Vector Machines ◽  
Decision Making Problem ◽  
Simulation Results

Knowledge employee’s turnover forecast is a multi-criteria decision-making problem involving various factors. In order to forecast accurately turnover of knowledge employees, the potential support vector machines(P-SVM) is introduced to develop a turnover forecast model. In the model development, a chaos algorithm and a genetic algorithm (GA) are employed to optimize P-SVM parameters selection. The simulation results show that the model based on potential support vector machine with chaos not only has much stronger generalization ability but also has the ability of feature selection.

Multi-objective integrated planning and scheduling model for operating rooms under uncertainty

2018 ◽  
Vol 232 (9) ◽  
pp. 930-948 ◽  
Author(s):  
Javad Ansarifar ◽  
Reza Tavakkoli-Moghaddam ◽  
Faezeh Akhavizadegan ◽  
Saman Hassanzadeh Amin
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Particle Swarm Optimization ◽  
Heuristic Algorithms ◽  
Particle Swarm ◽  
Operating Rooms ◽  
Programming Approach ◽  
Test Problems ◽  
Swarm Optimization ◽  
Multi Objective

This article formulates the operating rooms considering several constraints of the real world, such as decision-making styles, multiple stages for surgeries, time windows for resources, and specialty and complexity of surgery. Based on planning, surgeries are assigned to the working days. Then, the scheduling part determines the sequence of surgeries per day. Moreover, an integrated fuzzy possibilistic–stochastic mathematical programming approach is applied to consider some sources of uncertainty, simultaneously. Net revenues of operating rooms are maximized through the first objective function. Minimizing a decision-making style inconsistency among human resources and maximizing utilization of operating rooms are considered as the second and third objectives, respectively. Two popular multi-objective meta-heuristic algorithms including Non-dominated Sorting Genetic Algorithm and Multi-Objective Particle Swarm Optimization are utilized for solving the developed model. Moreover, different comparison metrics are applied to compare the two proposed meta-heuristics. Several test problems based on the data obtained from a public hospital located in Iran are used to display the performance of the model. According to the results, Non-dominated Sorting Genetic Algorithm-II outperforms the Multi-Objective Particle Swarm Optimization algorithm in most of the utilized metrics. Moreover, the results indicate that our proposed model is more effective and efficient to schedule and plan surgeries and assign resources than manual scheduling.

Genetic Algorithms for Decision-Making in Cognitive Radio Networks

2013 ◽  
pp. 247-263
Author(s):  
Tommy Hult ◽  
Abbas Mohammed
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Genetic Algorithms ◽  
Cognitive Radio ◽  
Search Space ◽  
Radio Spectrum ◽  
Dynamic Decision Making ◽  
Optimal Point ◽  
Optimization Search

Efficient use of the available licensed radio spectrum is becoming increasingly difficult as the demand and usage of the radio spectrum increases. This usage of the spectrum is not uniform within the licensed band but concentrated in certain frequencies of the spectrum while other parts of the spectrum are inefficiently utilized. In cognitive radio environments, the primary users are allocated licensed frequency bands while secondary cognitive users dynamically allocate the empty frequencies within the licensed frequency band according to their requested QoS (Quality of Service) specifications. This dynamic decision-making is a multi-criteria optimization problem, which the authors propose to solve using a genetic algorithm. Genetic algorithms traverse the optimization search space using a multitude of parallel solutions and choosing the solution that has the best overall fit to the criteria. Due to this parallelism, the genetic algorithm is less likely than traditional algorithms to get caught at a local optimal point.

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