Browsing by Subject "Q-learning"
Now showing items 1-11 of 11
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Distributed cooperative q-learning for power allocation in cognitive femtocell networks
( IEEE , 2012 , Conference)In this paper, we propose a distributed reinforcement learning (RL) technique called distributed power control using Q-learning (DPC-Q) to manage the interference caused by the femtocells on macro-users in the downlink. ... -
Ensemble artificial bee colony algorithm with Q-learning for scheduling Bi-objective disassembly line
( Elsevier , 2024 , Article)This study addresses a bi-objective disassembly line scheduling problem (Bi-DLSP), considering interference relationships among tasks. The objectives are to optimize the total disassembly time and the smoothing index ... -
Ensemble meta-heuristics and Q-learning for staff dissatisfaction constrained surgery scheduling and rescheduling
( Elsevier , 2024 , Article)In this study, we investigate the multi-objective surgery scheduling and rescheduling problems with considering medical staff dissatisfaction and fuzzy surgery time. Rescheduling is activated when emergency patients arrive. ... -
Integrated scheduling of multi-constraint open shop and vehicle routing: Mathematical model and learning-driven brain storm optimization algorithm
( Elsevier , 2024 , Article)Recent years have witnessed a surge of interest in integrated production and distribution scheduling problems which can achieve an overall optimization of the production and distribution activities. However, integrated ... -
Optimal cooperative cognitive relaying and spectrum access for an energy harvesting cognitive radio: Reinforcement learning approach
( Institute of Electrical and Electronics Engineers Inc. , 2015 , Conference)In this paper, we consider a cognitive setting under the context of cooperative communications, where the cognitive radio (CR) user is assumed to be a self-organized relay for the network. The CR user and the primary user ... -
Problem feature based meta-heuristics with Q-learning for solving urban traffic light scheduling problems
( Elsevier , 2023 , Article)An urban traffic light scheduling problem (UTLSP) is studied by using problem feature based meta-heuristics with Q-learning. The goal is to minimize the network-wise total delay time within a time window by finding a ... -
Problem-Specific Knowledge Based Multi-Objective Meta-Heuristics Combined Q-Learning for Scheduling Urban Traffic Lights With Carbon Emissions
( Institute of Electrical and Electronics Engineers Inc. , 2024 , Article)In complex and variable traffic environments, efficient multi-objective urban traffic light scheduling is imperative. However, the carbon emission problem accompanying traffic delays is often neglected in most existing ... -
Robust Enhancement of Intrusion Detection Systems Using Deep Reinforcement Learning and Stochastic Game
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)The incorporation of advanced networking technologies makes modern systems vulnerable to cyber-attacks that can result in a number of harmful outcomes. Due to the increase of security incidents and massive activities on ... -
Scheduling Eight-Phase Urban Traffic Light Problems via Ensemble Meta-Heuristics and Q-Learning Based Local Search
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)This paper addresses urban traffic light scheduling problems (UTLSP) with eight phases. The objective is to minimize the total vehicle delay time by assigning traffic phases and phase-timing optimally. A novel hybrid ... -
Scheduling Multiobjective Dynamic Surgery Problems via Q-Learning-Based Meta-Heuristics
( Institute of Electrical and Electronics Engineers Inc. , 2024 , Article)This work addresses multiobjective dynamic surgery scheduling problems with considering uncertain setup time and processing time. When dealing with them, researchers have to consider rescheduling due to the arrivals of ... -
Smart and Secure Blockchain-based Healthcare System Using Deep Q-Learning
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference)Healthcare is one of the top priorities in modern society to provide better health facilities. Therefore, investments in health care systems increased rapidly, aligned with the population growth rate. Besides, the data ...