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In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, causal inference, etc.
A system on a chip or system-on-chip is an integrated circuit that integrates most or all components of a computer or other electronic system. These components almost always include on-chip central processing unit (CPU), memory interfaces, input/output devices and interfaces, and secondary storage interfaces, often alongside other components such as radio modems and a graphics processing unit (GPU) – all on a single substrate or microchip. SoCs may contain digital and also analog, mixed-signal and often radio frequency signal processing functions.
Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. For large numbers of local optima, SA can find the global optima. It is often used when the search space is discrete. For problems where finding an approximate global optimum is more important than finding a precise local optimum in a fixed amount of time, simulated annealing may be preferable to exact algorithms such as gradient descent or branch and bound.
In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select a heuristic that may provide a sufficiently good solution to an optimization problem or a machine learning problem, especially with incomplete or imperfect information or limited computation capacity. Metaheuristics sample a subset of solutions which is otherwise too large to be completely enumerated or otherwise explored. Metaheuristics may make relatively few assumptions about the optimization problem being solved and so may be usable for a variety of problems.
Arena is a discrete event simulation and automation software developed by Systems Modeling and acquired by Rockwell Automation in 2000. It uses the SIMAN processor and simulation language. As of 2020, it is in version 16. It has been suggested that Arena may join other Rockwell software packages under the "FactoryTalk" brand.
Stochastic optimization (SO) are optimization methods that generate and use random variables. For stochastic optimization problems, the objective functions or constraints are random. Stochastic optimization also include methods with random iterates. Some hybrid methods use random iterates to solve stochastic problems, combining both meanings of stochastic optimization. Stochastic optimization methods generalize deterministic methods for deterministic problems.
Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mock up of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome.
AnyLogic is a multimethod simulation modeling tool developed by The AnyLogic Company. It supports agent-based, discrete event, and system dynamics simulation methodologies. AnyLogic is cross-platform simulation software that works on Windows, macOS and Linux. AnyLogic is used to simulate: markets and competition, healthcare, manufacturing, supply chains and logistics, retail, business processes, social and ecosystem dynamics, defense, project and asset management, pedestrian dynamics and road traffic, IT, and aerospace. It is considered to be among the major players in the simulation industry, especially within the domain of business processes is acknowledged to be a powerful tool.
SIMUL8 simulation software is a product of the SIMUL8 Corporation used for simulating systems that involve processing of discrete entities at discrete times. This program is a tool for planning, design, optimization and reengineering of real production, manufacturing, logistic or service provision systems. SIMUL8 allows its user to create a computer model, which takes into account real life constraints, capacities, failure rates, shift patterns, and other factors affecting the total performance and efficiency of production. Through this model it is possible to test real scenarios in a virtual environment, for example simulate planned function and load of the system, change parameters affecting system performance, carry out extreme-load tests, verify by experiments the proposed solutions and select the optimal solution. A common feature of problems solved in SIMUL8 is that they are concerned with cost, time and inventory.
Plant Simulation is a computer application developed by Siemens Digital Industries Software for modelling, simulating, analyzing, visualizing and optimizing production systems and processes, the flow of materials and logistic operations. Plant Simulation, allows users to optimize material flow and resource utilization and logistics for all levels of plant planning from global production facilities, through local plants, to specific lines. Within the Plant Design and Optimization Solution, the software portfolio, to which Plant Simulation belongs, is — together with the products of the Digital Factory and of Digital Manufacturing — part of the Product Lifecycle Management Software (PLM). The application allows comparing complex production alternatives, including the immanent process logic, by means of computer simulations. Plant Simulation is used by individual production planners as well as by multi-national enterprises, primarily to strategically plan layout, and control logic and dimensions of large, complex production investments. It is one of the major products that dominate that market space.
Fred Glover is Chief Scientific Officer of Entanglement, Inc., USA, in charge of algorithmic design and strategic planning for applications of combinatorial optimization in quantum computing. He also holds the title of Distinguished University Professor, Emeritus, at the University of Colorado, Boulder, associated with the College of Engineering and Applied Science and the Leeds School of Business. He is known for his innovations in the area of metaheuristics including the computer-based optimization methodology of Tabu search an adaptive memory programming algorithm for mathematical optimization, and the associated evolutionary Scatter Search and Path Relinking algorithms.
FlexSim is a discrete-event simulation software package developed by FlexSim Software Products, Inc. The FlexSim product family currently includes the general purpose FlexSim product and healthcare systems modeling environment.
Lanner Group Ltd is a software company specialising in simulation software such as discrete event simulation and predictive simulation, headquartered in Birmingham, UK. The business develops, markets and supports business process simulation and optimisation systems. The company has subsidiaries in the US, China, France and Germany and a distributor network selling the company's products in 20 different countries. Lanner Group was formed following a Management Buyout of AT&T Istel, a spin-off from the operational research department of British Leyland where, in 1978, the world's first visual interactive simulation tool was developed. Lanner Group services automotive, aviation, criminal justice, defence and aerospace, financial services and contact centres, food and beverage, health, logistics and supply chain, manufacturing, nuclear, oil and gas, pharmaceutical, and consumer health industries.
HeuristicLab is a software environment for heuristic and evolutionary algorithms, developed by members of the Heuristic and Evolutionary Algorithm Laboratory (HEAL) at the University of Applied Sciences Upper Austria, in Hagenberg im Mühlkreis. HeuristicLab has a strong focus on providing a graphical user interface so that users are not required to have comprehensive programming skills to adjust and extend the algorithms for a particular problem. In HeuristicLab algorithms are represented as operator graphs and changing or rearranging operators can be done by drag-and-drop without actually writing code. The software thereby tries to shift algorithm development capability from the software engineer to the user and practitioner. Developers can still extend the functionality on code level and can use HeuristicLab's plug-in mechanism that allows them to integrate custom algorithms, solution representations or optimization problems.
Optimus is a Process Integration and Design Optimization (PIDO) platform developed by Noesis Solutions. Noesis Solutions takes part in key research projects, such as PHAROS and MATRIX.
Simulation-based optimization integrates optimization techniques into simulation modeling and analysis. Because of the complexity of the simulation, the objective function may become difficult and expensive to evaluate. Usually, the underlying simulation model is stochastic, so that the objective function must be estimated using statistical estimation techniques.
Micro Saint Sharp is a general purpose discrete-event simulation and human performance modeling software tool developed by Alion Science and Technology. It is developed using C# and the .NET Framework. Micro Saint Sharp allows users to create discrete-event simulations as visual task networks with logic defined using the C# programming language.
LineLab is a software product for modeling, simulating and optimizing systems characterized by complex, stochastic flow behavior. The software is used to help with trade studies, exploring feasible throughput and required investment in complex, high-mix production settings, and to validate new business cases. It is utilized in different industries including aerospace, semiconductor manufacturing, and green tech.
References
- 1 2 3 4 5 6 7 Law, Averill M. (2015). Simulation modeling and analysis. McGraw-Hill series in industrial engineering and management science (5th ed.). New York, NY: McGraw-Hill Education. ISBN 978-0-07-340132-4.
- 1 2 Kleijnen, Jack P.C.; Wan, Jie (March 2007). "Optimization of simulated systems: OptQuest and alternatives". Simulation Modelling Practice and Theory. 15 (3): 354–362. doi:10.1016/j.simpat.2006.11.001. ISSN 1569-190X.
- 1 2 3 Jerbi, Abdessalem; Ammar, Achraf; Krid, Mohamed; Salah, Bashir (November 2019). "Performance optimization of a flexible manufacturing system using simulation: the Taguchi method versus OptQuest". Simulation. 95 (11): 1085–1096. doi:10.1177/0037549718819804. ISSN 0037-5497.
- ↑ Glover, Fred; Kelly, James; Laguna, Manuel (January 1998). The Optquest approach to Crystal Ball simulation optimization.
- ↑ "AnyLogic Timeline – AnyLogic Simulation Software".
- ↑ Eskandari, Hamidreza; Mahmoodi, Ehsan; Fallah, Hamed; Geiger, Christopher D. (December 2011). "Performance analysis of comercial simulation-based optimization packages: OptQuest and Witness Optimizer". Proceedings of the 2011 Winter Simulation Conference (WSC). IEEE. pp. 2358–2368. doi:10.1109/wsc.2011.6147946. ISBN 978-1-4577-2109-0.
- ↑ Jafferali, Mohammed; Venkateshwaran, Jayendran; Son, Young Jun (2005). "Performance comparison of search-based simulation optimisation algorithms for operations scheduling". International Journal of Simulation and Process Modelling. 1 (1/2): 58. doi:10.1504/IJSPM.2005.007114. ISSN 1740-2123.
- ↑ Eskandari, Hamidreza; Mahmoodi, Ehsan; Fallah, Hamed; Geiger, Christopher D. (2011). "Performance analysis of comercial simulation-based optimization packages: Optquest and Witness Optimizer". Proceedings of the Winter Simulation Conference (WSC '11): 2363–2373.
