Essays about: "Heuristic Optimisation"

Showing result 1 - 5 of 16 essays containing the words Heuristic Optimisation.

  1. 1. Machine Learning-Based Instruction Scheduling for a DSP Architecture Compiler : Instruction Scheduling using Deep Reinforcement Learning and Graph Convolutional Networks

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Lucas Alava Peña; [2023]
    Keywords : Instruction Scheduling; Deep reinforcement Learning; Compilers; Graph Convolutional Networks; Schemaläggning av instruktioner; Deep Reinforcement Learning; kompilatorer; grafkonvolutionella nätverk;

    Abstract : Instruction Scheduling is a back-end compiler optimisation technique that can provide significant performance gains. It refers to ordering instructions in a particular order to reduce latency for processors with instruction-level parallelism. READ MORE

  3. 2. Contributions to a New CBLS Backend for MiniZinc

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Maarten Lucas Flippo; [2022]
    Keywords : ;

    Abstract : MiniZinc is a language which enables the modelling of combinatorial optimisation and satisfaction problems independently from any particular problem solver and its technology. One technology for solving combinatorial optimisation and satisfaction problems is constraint-based local search (CBLS). READ MORE

  4. 3. Lagrangian Bounding and Heuristics for Bi-Objective Discrete Optimisation

    University essay from Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

    Author : Ida Åkerholm; [2022]
    Keywords : Lagrangian relaxation; bi-objective optimisation; Pareto frontier; heuristics; discrete optimisation;

    Abstract : For larger instances of multi-objective optimisation problems, the exact Pareto frontier can be both difficult and time-consuming to calculate. There is a wide range of methods to find feasible solutions to such problems, but techniques for finding good optimistic bounds to compare the feasible solutions with are missing. READ MORE

  5. 4. Task Scheduling Using Discrete Particle Swarm Optimisation

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Hampus Karlberg; [2020]
    Keywords : Scheduling; Discrete Particle Swarm Optimisation; Wireless Networks; Meta Heuristic; Machine Learning; Schemaläggning; diskret Particle Swarm Optimisation; Trådlösa Nätverk; Metaheurestik; Maskininlärning;

    Abstract : Optimising task allocation in networked systems helps in utilising available resources. When working with unstable and heterogeneous networks, task scheduling can be used to optimise task completion time, energy efficiency and system reliability. The dynamic nature of networks also means that the optimal schedule is subject to change over time. READ MORE

  6. 5. Applicability of Constraint Solving and Simulated Annealing to Real-World Scale University Course Timetabling Problems

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Felix Almay; Oskar Strömberg; [2019]
    Keywords : ;

    Abstract : The university course timetabling problem is the problem of creating a schedule for university courses under certain constraints. The decision variant of this optimisation problem is NP-complete. We have researched this problem and implemented the heuristic simulated annealing. READ MORE