Trade-Off Between Mental Map and Aesthetic Criteria in Simulated Annealing Based Graph Layout Algorithms

2018 ◽  
pp. 110-125
Author(s):  
Armin Jörg Slopek ◽  
Carsten Winkelholz ◽  
Margaret Varga
Keyword(s):  
Simulated Annealing ◽  
Graph Layout ◽  
Trade Off ◽  
Mental Map

scholarly journals Feasibility Study on Measuring the Particulate Matter Level in the Atmosphere by Means of Yagi–Uda-Like Antennas

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3225 ◽  
Author(s):  
Aarón A. Salas-Sánchez ◽  
Julian Rauch ◽  
M. Elena López-Martín ◽  
J. Antonio Rodríguez-González ◽  
Giorgio Franceschetti ◽  
...  
Keyword(s):  
Dielectric Constant ◽  
Simulated Annealing ◽  
Method Of Moments ◽  
Surrounding Medium ◽  
Measurement Procedure ◽  
Characteristic Parameters ◽  
Trade Off ◽  
Promising Solution ◽  
Moderate Length ◽  
Concentration Levels

In this work, the application of a technique for monitoring changes of the dielectric constant of the atmosphere caused by the presence of pollution is discussed. The method is based on changes in the reflection coefficient of the device induced by these dielectric constant variations of the surrounding medium. To that end, several Yagi–Uda-like antenna designs with different size limitations were simulated by using a Method-of-Moments software and optimized by means of a simulated annealing strategy. It has been found that the larger the optimal elements of the array are allowed to be, the higher the sensitivity reached. Thus, in a trade-off between sensitivity and moderate length (regarding flexibility purposes), the most promising solution has been built. This prototype has been experimentally tested in presence of an artificial aerosol made of PAO (polyalphaolefin) oil and black carbon inclusions of a size of 0.2 μm. As a result, potentials for developing a measurement procedure by means of changes in the characteristic parameters of the antenna led by different concentration levels of suspended particles in the surrounding medium are shown. In this manner, a local mapping of polluted levels could be developed in an easy, real-time, and flexible procedure.

Mental map preserving graph drawing using simulated annealing

2011 ◽  
Vol 181 (19) ◽  
pp. 4253-4272 ◽  
Author(s):  
Chun-Cheng Lin ◽  
Yi-Yi Lee ◽  
Hsu-Chun Yen
Keyword(s):  
Simulated Annealing ◽  
Graph Drawing ◽  
Mental Map

Energy Efficient Scheduling Using Simulated Annealing Algorithm for Multi-Core Processors

2014 ◽  
Vol 550 ◽  
pp. 178-186
Author(s):  
M. Poongothai ◽  
A. Rajeswari ◽  
V. Sanmukapriya
Keyword(s):  
Simulated Annealing ◽  
Power Dissipation ◽  
System Performance ◽  
Heat Dissipation ◽  
Simulated Annealing Algorithm ◽  
Thermal Conditions ◽  
Global Optimum ◽  
Battery Life ◽  
Trade Off ◽  
Annealing Algorithm

The role of multi-core processors in recently developed real-time systems is gaining importance because of its energy and thermal conditions. The major development requirements and objectives to be met while designing multi-core processors are: low heat dissipation, low energy consumption and long battery life, which also helps to reduce the system costs. This paper is presented with an aim to achieve a better system performance in a multi-core processor platform by adjusting the trade-off between system performance and power dissipation. Dynamic Power Management (DPM) and Dynamic Voltage Scaling (DVS) are the two run-time techniques used to adjust the trade-off between the system performance and power dissipation. Simulated Annealing (SA) algorithm is implemented in order to find a good approximation to the global optimum. The idea behind Simulated Annealing algorithm is to iteratively improve the solution by investigating the neighbour solutions.

A Framework for Time-Cost-Quality Optimization in Project Management Problems Using an Exploratory Grid Concept in the Multi-Objective Simulated-Annealing

2021 ◽  
pp. 1-26
Author(s):  
Alzira Mota ◽  
Paulo Ávila ◽  
Ricardo Albuquerque ◽  
Lino Costa ◽  
João Bastos
Keyword(s):  
Decision Making ◽  
Simulated Annealing ◽  
Optimization Problems ◽  
Decision Makers ◽  
Time Cost ◽  
Trade Off ◽  
Multi Objective ◽  
Pareto Optimal Set ◽  
Criteria Weights ◽  
Optimal Set

Time, cost, and quality are the three indispensable factors for the realization and success of a project. In this context, we propose a framework composed of a multi-objective approach and multi-criteria decision-making methods (MCDM) to solve time-cost-quality trade-off optimization problems. A multi-objective Simulated Annealing (MOSA) algorithm is used to compute an approximation to the Pareto optimal set. The concept of the exploratory grid is introduced in the MOSA to improve its performance. MCDM are used to assist the decision-making process. The Shannon entropy and AHP methods assign weights to criteria. The first methodology is for the inexperienced decision-makers, and the second concedes a personal and flexible weighting of the criteria weights, based on the project manager’s assessment. The TOPSIS and VIKOR methods are considered to rank the solutions. Although they have the same purpose, the rankings achieved are different. A tool is implemented to solve a time-cost-quality trade-off problem on a project activities network. The computational experiments are analyzed and the results with the exploratory grid in Simulated Annealing (SA) are promising. Despite the framework aims to solve multi-objective trade-off optimization problems, supporting the decisions of the project manager, the methodologies used can also be applied in other areas.

Time-cost trade off in cpm networks by simulated annealing

2001 ◽  
Vol 1 (3) ◽  
pp. 315-329 ◽  
Author(s):  
K. P. Anagnostopoulos ◽  
L. Kotsikas
Keyword(s):  
Simulated Annealing ◽  
Time Cost ◽  
Trade Off

scholarly journals Improving cross-docking operations for consumer goods sector using metaheuristics

2021 ◽  
Vol 10 (1) ◽  
pp. 524-532
Author(s):  
Rodrigo Andrés Gómez- Montoya ◽  
Jose Alejandro Cano ◽  
Emiro Antonio Campo ◽  
Fernando Salazar
Keyword(s):  
Particle Swarm Optimization ◽  
Simulated Annealing ◽  
Consumer Goods ◽  
Efficient Solution ◽  
Solution Method ◽  
Swarm Optimization ◽  
Response Variable ◽  
Trade Off ◽  
Cross Docking ◽  
The Cross

This paper aims to model a consumer goods cross-docking problem, which is solved using metaheuristics to minimize makespan and determine the capacity in terms of inbound and outbound docks. The consumer-goods cross-docking problem is represented through inbound and outbound docks, customer orders (products to be delivered to customers), and metaheuristics as a solution method. Simulated annealing (SA) and particle swarm optimization (PSO) are implemented to solve the cross-docking problem. Based on the results of statistical analysis, it was identified that the two-way interaction effect between inbound and outbound docks, outbound docks and items, and items and metaheuristics are the most statistically significant on the response variable. The best solution provides the minimum makespan of 973.42 minutes considering nine inbound docks and twelve outbound docks. However, this study detected that the combination of six inbound docks and nine outbound docks represents the most efficient solution for a cross-docking design since it reduces the requirement of docks by 28.6% and increases the makespan by only 4.2% when compared to the best solution, representing a favorable trade-off for the cross-docking platform design. 

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