Specification of Evolutionary Algorithm under Constraints Post-Filtering/Ordering

Christoph Georg Schütz, Samuel Jaburek

Research output: Working paper and reportsResearch report

Abstract

The SlotMachine system employs an evolutionary algorithm in conjunction with multiparty computation to optimize flight lists in a privacy-preserving way. This document describes the Heuristic Optimizer component of the SlotMachine system, which realizes the evolutionary algorithm for finding solutions to the SlotMachine flight prioritization problem. The Heuristic Optimizer provides an extendable framework allowing to plug in different implementations of evolutionary algorithms for optimization of flight lists; this document describes a configurable genetic algorithm implementation. Experiments conducted with generated synthetic data for different scenarios serve to evaluate the implementation of the Heuristic Optimizer. Keywords: Air traffic flow management, evolutionary algorithm, genetic algorithm, assignment problem, privacy Technical Report, Projekt SELOTMACHINE, Deliverable D4.2, CORDIS - EU Research Results, Projekt-DOI: https://doi.org/10.3030/890456, 2022.
Original languageEnglish
PublisherInstitutsbericht, Johannes Kepler Universität Linz (JKU), Institut für Wirtschaftsinformatik - Data
Number of pages49
Publication statusPublished - 2022

Fields of science

  • 102 Computer Sciences
  • 102010 Database systems
  • 102015 Information systems
  • 102016 IT security
  • 102025 Distributed systems
  • 102027 Web engineering
  • 102028 Knowledge engineering
  • 102030 Semantic technologies
  • 102033 Data mining
  • 102035 Data science
  • 509026 Digitalisation research
  • 502050 Business informatics
  • 502058 Digital transformation
  • 503008 E-learning

JKU Focus areas

  • Digital Transformation

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