Results 51 to 60 of about 1,136 (193)

Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches

World Electric Vehicle Journal
This study addresses the optimization of the Vehicle Routing Problem (VRP) with prioritized customers by introducing and comparing two advanced solution approaches: a metaheuristic-based hyperheuristic framework and a Variational Autoencoder (VAE)-based ...
Kassem Danach, Louai Saker, Hassan Harb
doaj   +1 more source

Genetic algorithms with guided and local search strategies for university course timetabling [PDF]

, 2011
This article is posted here with permission from the IEEE - Copyright @ 2011 IEEEThe university course timetabling problem (UCTP) is a combinatorial optimization problem, in which a set of events has to be scheduled into time slots and located into ...
Jat, SN, Yang, S
core   +1 more source

Quantum-Inspired Hyperheuristic Framework for Solving Dynamic Multi-Objective Combinatorial Problems in Disaster Logistics

World Electric Vehicle Journal
Disaster logistics presents a highly complex decision-making challenge under conditions of uncertainty, where the timely and efficient allocation of scarce resources is essential to minimize human suffering.
Kassem Danach, Hassan Harb, Louai Saker, Ali Raad   +3 more
doaj   +1 more source

Hyper-Heuristic Approach for Improving Marker Efficiency

AUTEX Research Journal, 2018
Marker planning is an optimization arrangement problem, where a set of cutting parts need to be placed on a thin paper without overlapping to create a marker – an exact diagram of cutting parts that will be cut from a single spread.
Domović Daniel, Rolich Tomislav, Golub Marin   +2 more
doaj   +1 more source

Two-Stage Optimal Task Scheduling for Smart Home Environment Using Fog Computing Infrastructures

Applied Sciences, 2023
The connection of many devices has brought new challenges with respect to the centralized architecture of cloud computing. The fog environment is suitable for many services and applications for which cloud computing does not support these well, such as ...
Oshin Sharma, Geetanjali Rathee, Chaker Abdelaziz Kerrache, Jorge Herrera-Tapia   +3 more
doaj   +1 more source

Energy-Efficient Dynamic Vehicle Routing for Waste Collection by Q-Learning-Based Hyperheuristic Particle Swarm Optimization

IEEE Access
During the process of waste collection, various unpredicted disturbances might occur. Meanwhile, vehicle transport is an important source of carbon emissions.
Yun Zhao, Xiaoning Shen, Wenyan Chen, Hongli Pan   +3 more
doaj   +1 more source

A dynamic truck dispatching problem in marine container terminal [PDF]

, 2016
In this paper, a dynamic truck dispatching problem of a marine container terminal is described and discussed. In this problem, a few containers, encoded as work instructions, need to be transferred between yard blocks and vessels by a fleet of trucks ...
Bai, Ruibin, Chen, Jianjun, Dong, Haibo, Kendall, Graham, Qu, Rong   +4 more
core   +1 more source

A stochastic local search algorithm with adaptive acceptance for high-school timetabling [PDF]

, 2014
Automating high school timetabling is a challenging task. This problem is a well known hard computational problem which has been of interest to practitioners as well as researchers.
A Hertz, A Kannan, Ahmed Kheiri, Andrew J. Parkes, B McCollum, C Valouxis, D Abramson, D Abramson, D Pisinger, D Werra de, E Özcan, E Özcan, E Özcan, EK Burke, Ender Özcan, G Post, GN Beligiannis, H Fisher, HR Lourenço, K Chakhlevitch, KA Smith, M Luby, M Marte, S Broder, S Even, T Birbas   +25 more
core   +4 more sources

Combining Simulation and Gradient Boosted Trees for the Stochastic Permutation Flowshop Scheduling Problem

IET Collaborative Intelligent Manufacturing, Volume 7, Issue 1, January/December 2025.
The stochastic flowshop scheduling problem is addressed. An ML‐method to speed up the local search is proposed. ABSTRACT In this paper, we address a stochastic variant of the well‐known permutation flowshop scheduling problem, where the processing times of the jobs in the machines are assumed to be random variables.
Jose M. Framinan
wiley   +1 more source

Fuzzy hyperheuristic optimization of a facilitated hub-and-spoke drone-enabled logistics network: a case study of Australia Post

Frontiers in Applied Mathematics and Statistics
IntroductionThe rapid growth of e-commerce has increased pressure on postal logistics networks, especially in remote regions.MethodsThis study proposes a fuzzy hyperheuristic genetic algorithm for optimizing a facilitated hub-and-spoke network with drone
Kassem Danach, Samir Haddad, Wissam Khalil, Ziad El Balaa, Jinane Sayah   +4 more
doaj   +1 more source