Optimisation Methods in PASCAL

1988 ◽  
Vol 72 (461) ◽  
pp. 242
Author(s):  
R. Davison ◽  
Brian D. Bunday ◽  
Gerald R. Garside
Keyword(s):  
Optimisation Methods

Efficiency and fractal behaviour of optimisation methods on multiple-optima surfaces

1991 ◽  
Vol 36 (3) ◽  
pp. 315-328 ◽  
Author(s):  
D.G. Mayer ◽  
D. Schoorl ◽  
D.G. Butler ◽  
A.M. Kelly
Keyword(s):  
Fractal Behaviour ◽  
Optimisation Methods

scholarly journals Warpage Optimisation Using Recycled Polycar-bonates (PC) on Front Panel Housing

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1416
Author(s):  
Nur Aisyah Miza Ahmad Tamizi ◽  
Shayfull Zamree Abd Rahim ◽  
Abdellah El-hadj Abdellah ◽  
Mohd Mustafa Al Bakri Abdullah ◽  
Marcin Nabiałek ◽  
...  
Keyword(s):  
Simulation Analysis ◽  
Processing Parameters ◽  
Front Panel ◽  
Processing Parameter ◽  
Mechanical Recycling ◽  
Great Opportunity ◽  
Average Value ◽  
Optimal Processing ◽  
Materials Used ◽  
Optimisation Methods

Many studies have been done using recycled waste materials to minimise environmental problems. It is a great opportunity to explore mechanical recycling and the use of recycled and virgin blend as a material to produce new products with minimum defects. In this study, appropriate processing parameters were considered to mould the front panel housing part using R0% (virgin), R30% (30% virgin: 70% recycled), R40% (40% virgin: 60% recycled) and R50% (50% virgin: 50% recycled) of Polycarbonate (PC). The manufacturing ability and quality during preliminary stage can be predicted through simulation analysis using Autodesk Moldflow Insight 2012 software. The recommended processing parameters and values of warpage in x and y directions can also be obtained using this software. No value of warpage was obtained from simulation studies for x direction on the front panel housing. Therefore, this study only focused on reducing the warpage in the y direction. Response Surface Methodology (RSM) and Genetic Algorithm (GA) optimisation methods were used to find the optimal processing parameters. As the results, the optimal ratio of recycled PC material was found to be R30%, followed by R40% and R50% materials using RSM and GA methods as compared to the average value of warpage on the moulded part using R0%. The most influential processing parameter that contributed to warpage defect was packing pressure for all materials used in this study.

Holistic simulation-based optimisation methodology for facility layout design with consideration to production and logistics constraints

2021 ◽  
pp. 095440542110173
Author(s):  
Enrique Ruiz Zúñiga ◽  
Erik Flores García ◽  
Matías Urenda Moris ◽  
Masood Fathi ◽  
Anna Syberfeldt
Keyword(s):  
Material Handling ◽  
Facility Layout ◽  
Holistic Approach ◽  
Multiple Attribute Decision Making ◽  
Layout Design ◽  
Analytic Hierarchy ◽  
Facility Layout Design ◽  
Multiple Attribute ◽  
Simulation Based ◽  
Optimisation Methods

Facility layout design is becoming more challenging as manufacturing moves from traditionally emphasised mass production to mass customisation. The increasing demand for customised products and services is driving the need to increase flexibility and adaptability of both production processes and their material handling systems. A holistic approach for designing facility layouts with optimised flows considering production and logistics systems constraints seems to be missing in the literature. Several tools, including traditional methods, analytic hierarchy process, multiple-attribute decision making, simulation, and optimisation methods, can support such a process. Among these, simulation-based optimisation is the most promising. This paper aims to develop a facility layout design methodology supported by simulation-based optimisation while considering both production and logistics constraints. A literature review of facility layout design with simulation and optimisation and the theoretical and empirical challenges are presented. The integration of simulation-based optimisation in the proposed methodology serves to overcome the identified challenges, providing managers and stakeholders with a decision support system that handles the complex task of facility layout design.

Efficacy of modified backpropagation and optimisation methods on a real-world medical problem

1995 ◽  
Vol 8 (6) ◽  
pp. 945-962 ◽  
Author(s):  
Dogan Alpsan ◽  
Michael Towsey ◽  
Ozcan Ozdamar ◽  
Ah Chung Tsoi ◽  
Dhanjoo N. Ghista
Keyword(s):  
Real World ◽  
Medical Problem ◽  
Optimisation Methods

Improved Gauss-Newton optimisation methods in affine registration of SPECT brain images

2008 ◽  
Vol 44 (22) ◽  
pp. 1291 ◽  
Author(s):  
D. Salas-Gonzalez ◽  
J.M. Górriz ◽  
J. Ramírez ◽  
A. Lass ◽  
C.G. Puntonet
Keyword(s):  
Brain Images ◽  
Affine Registration ◽  
Optimisation Methods

scholarly journals Multi-Mode Wave Energy Converter Design Optimisation Using an Improved Moth Flame Optimisation Algorithm

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3737
Author(s):  
Mehdi Neshat ◽  
Nataliia Sergiienko ◽  
Seyedali Mirjalili ◽  
Meysam Majidi Nezhad ◽  
Giuseppe Piras ◽  
...  
Keyword(s):  
Wave Energy ◽  
Wave Energy Converter ◽  
Total Power ◽  
Energy Converter ◽  
Wave Regime ◽  
Optimisation Algorithm ◽  
Wide Range ◽  
Evolutionary Optimisation ◽  
Optimisation Methods ◽  
Optimisation Algorithms

Ocean renewable wave power is one of the more encouraging inexhaustible energy sources, with the potential to be exploited for nearly 337 GW worldwide. However, compared with other sources of renewables, wave energy technologies have not been fully developed, and the produced energy price is not as competitive as that of wind or solar renewable technologies. In order to commercialise ocean wave technologies, a wide range of optimisation methodologies have been proposed in the last decade. However, evaluations and comparisons of the performance of state-of-the-art bio-inspired optimisation algorithms have not been contemplated for wave energy converters’ optimisation. In this work, we conduct a comprehensive investigation, evaluation and comparison of the optimisation of the geometry, tether angles and power take-off (PTO) settings of a wave energy converter (WEC) using bio-inspired swarm-evolutionary optimisation algorithms based on a sample wave regime at a site in the Mediterranean Sea, in the west of Sicily, Italy. An improved version of a recent optimisation algorithm, called the Moth–Flame Optimiser (MFO), is also proposed for this application area. The results demonstrated that the proposed MFO can outperform other optimisation methods in maximising the total power harnessed from a WEC.

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