![]() ![]() ![]() AnyLogic HowTo Video: Optimisation Experiment.Lab: Implementing Simulation Optimisation Workshop: Optimisation Experiments in AnyLogic Lecture: Optimisation with ABM Simulation Workshop: Evaluating Heuristic Algorithms Lab: Exploring Simulation Optimisation Examples Workshop: Combining Simulation and Optimization Lecture: Constructive and Local Search Heuristics Workshop: AnyLogic - Beginner to Pro in under an hour ) Useful resource: Transentis's Introduction to System Dynamics with iThink.Lecture: System dynamics modelling and simulation + hybrids Workshop: Introduction to focus groups + Peer's research Useful resource: Jose Vidal's videos on ABM and MAS using NetLogo.Useful resource: Nathaniel Osgood's ABM Bootcamp slides.Lecture: Agent-based modelling and simulation Workshop: Validation and verification within the simulation life cycle + introduction to group activity Useful resource: SimioSimulation YouTube Chanel. ![]() Useful resource: Nathaniel Osgood's Discrete Event Modelling in AnyLogic.Lecture: Discrete event modelling and simulation Workshop: Data and information + representing unpredictable variability Homework: Watch the following video >Inaugural Lecture of Professor Stewart Robinson<< Lecture: Conceptual modelling + conceptual modelling exercise Workshop: Working with AnyLogic and Java Lecture: Introduction to AnyLogic and Java Lecture: Introduction to simulation and optimisation (the bigger picture) I teach this module together with my colleague Dario Landa-Silva. If you are one of my COMP4038 students, please use Moodle instead of this website, as the slides here contain lots of spoilers for the in-class activities. Throughout the module, you will become more competent in choosing and implementing the appropriate method(s) for the particular problem at hand. The foundations for applying these methods are derived from Operations Research Simulation, Social Simulation, Data Science, Automated Scheduling, and Decision Analysis. This module offers insight into the applications of selected methods of decision support. Public virtual ExtensionRegistry GetQualityMessageExtensions() cannot be added to the message", variable.G54SOD: Simulation and Optimisation for Decision Support Private object clientLock = new object() Anylogic shows 300, HL shows 1360 iterations). Somehow HeuristicLab shows a lot more evaluated solutions than Anylogic actually evaluated.ฤก) HeuristicLab shows thoughout the optimization run more evaluated solutions than Anylogic, until the the predefined amount of iterations (from Anylogic) is reached (e.g. But the programmable problem with external evaluation shows some weird behavior. In Anylogic I set the number of iterations for the experiment and with the ""regular" External Evaluation Problem (single-objective) everything works just fine. I assume both, with the same Integer bounds and Integer length and without any feasibility checks or repair functions, should now work the same using a genetic algorithm with the same algorithm parameters. One is the programmable problem (single objective) with external evaluation (the one we talked about in the upper posts) and the other one is a "regular" External Evaluation Problem (single-objective). I have another issue regarding the programmable problem. I have to do some investigating tomorrow. Thanks for your reply! I did some testing and the error seems to be somewhere in my repair code. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |