Open AccessFuzzy-controller simulation model as a tool of optimization of a limited availability ground handling system at a hub airport
Author(s) -
В. А. Романенко
Publication year - 2020
Publication title -
vestnik samarskogo universiteta. aèrokosmičeskaâ tehnika, tehnologii i mašinostroenie
Language(s) - English
Resource type - Journals
eISSN - 2541-7533
pISSN - 2542-0453
DOI - 10.18287/2541-7533-2019-18-4-169-177
Subject(s) - process (computing) , fuzzy logic , operator (biology) , task (project management) , controller (irrigation) , probabilistic logic , operations research , computer science , resource (disambiguation) , industrial engineering , optimization problem , mathematical optimization , simulation , engineering , systems engineering , artificial intelligence , computer network , agronomy , biochemistry , chemistry , repressor , biology , transcription factor , gene , operating system , mathematics , algorithm
The task of optimizing the optimal quantity of technological resources of a hub airport’s functional subsystem, executing an individual process step of ground handling, is considered. This problem is relevant to hub airports. The analysis is limited to limited availability systems in which handling of certain orders can be performed only by certain resources which are used in reference to automated and mechanical equipment, industrial equipment, personnel, etc. The optimization problem is formulated in a probabilistic statement. An approach to solving the problem is described. We suggest using a simulation computer model as an optimization tool. The model takes into account the features of passenger flows and the operating process of a hub airport and includes a fuzzy controller that reflects the logic of the airport operator who controls the ground handling process. The paper describes a model example of solving an optimization problem indicating the possibility and expedience of using a fuzzy controller as a model for the strategy of a human operator. Time dependence of the quantity of technological resources of the functional subsystem is the main result of optimization. This dependence is applicable at the stages of making decisions concerning increase of its capacity rate, operative resource management, planning staff shift work, solving a number of other tasks, especially relevant for hub airports with intense but non-uniform flows of aircraft and passengers.