scholarly journals IMPROVEMENT OF PICK-UP ROUTES FOR AN INTERNATIONAL SHIPPING ENTERPRISE BY USING A HEURISTIC METHOD

2016 ◽  
Vol 4 (6) ◽  
pp. 58
Author(s):  
Mario-Alberto Durán-Mendez ◽  
Santiago-Omar Caballero-Morales ◽  
José-Luiz Martínez-Flores ◽  
Patricia Cano-Olivos
Keyword(s):  
Heuristic Method ◽  
International Shipping ◽  
Shipping Enterprise

scholarly journals Charter Market Segmentation in Response to Trade’s Needs

2020 ◽  
pp. 78-87
Author(s):  
Evi Plomaritou ◽  
Angelos Menelaou
Keyword(s):  
Market Segmentation ◽  
Transport Service ◽  
Market Segments ◽  
Sea Transport ◽  
International Shipping ◽  
Commercial Success ◽  
Transport Services ◽  
Segmentation Approach ◽  
Buying Behaviour ◽  
Shipping Enterprise

Chartering is the part of international shipping business which broadly deals with the proper matching of cargoes’ transport needs and vessels’ commercial trading. Different charterers have different transportation needs. They do not all require the same sea transport service and not all charterers charter a particular vessel for the same reasons. Therefore, this paper intends to present how the charter market may be structured in response to trade’s needs and charterers’ requirements. The main objective of this paper is to constitute an overview of the shipping market segmentation into the various market segments. The analysis is based on the behavioural segmentation approach. This paper discusses mainly the conditions of charter market segmentation through relevant theories, reviews and some real cases analyses. Segmentation involves homogeneous buying behaviour of charterers within a segment but heterogeneous buying behaviour between segments. In respect of the trade’s needs, emphasis is given on charterers’ requirements in bulk market (dry and liquid) and on shippers’ requirements in liner market. Furthermore, the paper examines how the shipping companies should respond to their clients’ demands. Shipping enterprises have unique capabilities concerning the means, the resources and the management abilities for their ships. The matching of the shipping enterprise capabilities with the needs and the desires of its clients is fundamental for the provision of the desired transport services, the satisfaction and retention of charterers and thus the commercial success of the enterprise. Main objective of charter market segmentation is to assist the company focus its efforts to the most promising opportunities.

A Heuristic Method Based on Multi-Objective Optimization Concept for Solving RNA Multiple Alignment

2017 ◽  
Vol 10 (5) ◽  
pp. 371
Author(s):  
Arakil Chentoufi ◽  
Abdelhakim El Fatmi ◽  
Molay Ali Bekri ◽  
Said Benhlima ◽  
Mohamed Sabbane
Keyword(s):  
Heuristic Method ◽  
Multiple Alignment ◽  
Multi Objective Optimization ◽  
Multi Objective

scholarly journals The bond and retention of Chinese seafarers for international shipping companies: a survey report

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Bin Wu ◽  
Glory Gu ◽  
Chris James Carter
Keyword(s):  
Career Satisfaction ◽  
Organizational Values ◽  
Retention Rates ◽  
Management Systems ◽  
Policy Recommendations ◽  
Mutual Trust ◽  
Shipping Company ◽  
International Shipping ◽  
Survey Report ◽  
Chinese Seafarers

AbstractThe shortage of junior seafarers in China in recent years raises a salient question as to how international shipping companies can improve retention rates among Chinese crews. This issue has become increasingly prominent in the context of a global lockdown resulting from the Covid-19 pandemic. This paper examines the dilemma through the lens of the “bond” between seafarers and the shipping companies they service, a term used to reflect the need to recognise, consent and integrate into management systems, safety culture, and organizational values. The value of this bond concept is investigated in a survey of Chinese crews (N = 318). The paper aims to reveal the features and underlying factors of the bond, and its influence on needs, perceptions and seafaring careers in foreign shipping companies. The study finds that the majority of respondents do not have a bond with their shipping company, but typically do wish to develop one. Furthermore, this form of attachment appears to be closely related to career satisfaction and retention. To address the shortage of junior seafarers in China, we call for the development of mutual trust, respect and shared values between global seafarers and international shipping companies. A number of policy recommendations are provided.

scholarly journals gbt-HIPS: Explaining the Classifications of Gradient Boosted Tree Ensembles

2021 ◽  
Vol 11 (6) ◽  
pp. 2511
Author(s):  
Julian Hatwell ◽  
Mohamed Medhat Gaber ◽  
R. Muhammad Atif Azad
Keyword(s):  
State Of The Art ◽  
Heuristic Method ◽  
Good Explanation ◽  
Classification Rule ◽  
Data Sets ◽  
Classification Models ◽  
Boundary Values ◽  
Class Label ◽  
Input Space ◽  
Boosted Tree

This research presents Gradient Boosted Tree High Importance Path Snippets (gbt-HIPS), a novel, heuristic method for explaining gradient boosted tree (GBT) classification models by extracting a single classification rule (CR) from the ensemble of decision trees that make up the GBT model. This CR contains the most statistically important boundary values of the input space as antecedent terms. The CR represents a hyper-rectangle of the input space inside which the GBT model is, very reliably, classifying all instances with the same class label as the explanandum instance. In a benchmark test using nine data sets and five competing state-of-the-art methods, gbt-HIPS offered the best trade-off between coverage (0.16–0.75) and precision (0.85–0.98). Unlike competing methods, gbt-HIPS is also demonstrably guarded against under- and over-fitting. A further distinguishing feature of our method is that, unlike much prior work, our explanations also provide counterfactual detail in accordance with widely accepted recommendations for what makes a good explanation.

scholarly journals Towards 6G IoT: Tracing Mobile Sensor Nodes with Deep Learning Clustering in UAV Networks

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3936
Author(s):  
Yannis Spyridis ◽  
Thomas Lagkas ◽  
Panagiotis Sarigiannidis ◽  
Vasileios Argyriou ◽  
Antonios Sarigiannidis ◽  
...  
Keyword(s):  
Deep Learning ◽  
Heuristic Method ◽  
Sensor Nodes ◽  
Convolutional Network ◽  
Received Signal Strength Indicator ◽  
Anchor Nodes ◽  
Time Required ◽  
Rf Signal ◽  
Deep Learning Model

Unmanned aerial vehicles (UAVs) in the role of flying anchor nodes have been proposed to assist the localisation of terrestrial Internet of Things (IoT) sensors and provide relay services in the context of the upcoming 6G networks. This paper considered the objective of tracing a mobile IoT device of unknown location, using a group of UAVs that were equipped with received signal strength indicator (RSSI) sensors. The UAVs employed measurements of the target’s radio frequency (RF) signal power to approach the target as quickly as possible. A deep learning model performed clustering in the UAV network at regular intervals, based on a graph convolutional network (GCN) architecture, which utilised information about the RSSI and the UAV positions. The number of clusters was determined dynamically at each instant using a heuristic method, and the partitions were determined by optimising an RSSI loss function. The proposed algorithm retained the clusters that approached the RF source more effectively, removing the rest of the UAVs, which returned to the base. Simulation experiments demonstrated the improvement of this method compared to a previous deterministic approach, in terms of the time required to reach the target and the total distance covered by the UAVs.

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