A Heuristic Approach For Solving Container-on-Barge Stowage Planning Problem Based On Bin-Packing First-Fit Algorithm

2020 ◽  
Author(s):  
Amina El Yaagoubi ◽  
Ahmed El Hilali Alaoui ◽  
Jaouad Boukachour
Keyword(s):  
Bin Packing ◽  
Heuristic Approach ◽  
Planning Problem ◽  
Stowage Planning

A heuristic approach to the task planning problem in a home care business

2020 ◽  
Vol 23 (4) ◽  
pp. 556-570
Author(s):  
Isabel Méndez-Fernández ◽  
Silvia Lorenzo-Freire ◽  
Ignacio García-Jurado ◽  
Julián Costa ◽  
Luisa Carpente
Keyword(s):  
Home Care ◽  
Heuristic Approach ◽  
Planning Problem ◽  
Task Planning

The Terminal-Oriented Ship Stowage Planning Problem

2014 ◽  
Vol 239 (1) ◽  
pp. 256-265 ◽  
Author(s):  
Maria Flavia Monaco ◽  
Marcello Sammarra ◽  
Gregorio Sorrentino
Keyword(s):  
Planning Problem ◽  
Stowage Planning

scholarly journals A Deep Q-Learning Network for Ship Stowage Planning Problem

2017 ◽  
Vol 24 (s3) ◽  
pp. 102-109 ◽  
Author(s):  
Yifan Shen ◽  
Ning Zhao ◽  
Mengjue Xia ◽  
Xueqiang Du
Keyword(s):  
Planning Problem ◽  
Crane Scheduling ◽  
Online Searching ◽  
Q Learning ◽  
Learning Network ◽  
Reward Function ◽  
Algorithm Efficiency ◽  
Training Stage ◽  
Stowage Planning ◽  
Stowage Plan

Abstract Ship stowage plan is the management connection of quae crane scheduling and yard crane scheduling. The quality of ship stowage plan affects the productivity greatly. Previous studies mainly focuses on solving stowage planning problem with online searching algorithm, efficiency of which is significantly affected by case size. In this study, a Deep Q-Learning Network (DQN) is proposed to solve ship stowage planning problem. With DQN, massive calculation and training is done in pre-training stage, while in application stage stowage plan can be made in seconds. To formulate network input, decision factors are analyzed to compose feature vector of stowage plan. States subject to constraints, available action and reward function of Q-value are designed. With these information and design, an 8-layer DQN is formulated with an evaluation function of mean square error is composed to learn stowage planning. At the end of this study, several production cases are solved with proposed DQN to validate the effectiveness and generalization ability. Result shows a good availability of DQN to solve ship stowage planning problem.

scholarly journals Heuristic approach to the passive optical network with fibre duct sharing planning problem

ORiON ◽  
2015 ◽  
Vol 31 (2) ◽  
pp. 95 ◽  
Author(s):  
SP Van Loggerenberg ◽  
MJ Grobler ◽  
SE Terblanche
Keyword(s):  
Optical Network ◽  
Heuristic Approach ◽  
Passive Optical Network ◽  
Planning Problem

Solving the 3D stowage planning problem integrated with the quay crane scheduling problem by representation by rules and genetic algorithm

2018 ◽  
Vol 65 ◽  
pp. 495-516 ◽  
Author(s):  
Anibal Tavares Azevedo ◽  
Luiz Leduino de Salles Neto ◽  
Antônio Augusto Chaves ◽  
Antônio Carlos Moretti
Keyword(s):  
Genetic Algorithm ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Quay Crane Scheduling ◽  
Crane Scheduling ◽  
Stowage Planning
Sign in / Sign up

Export Citation Format

Share Document