Fleet deployment optimization for liner shipping Part 1. Background, problem formulation and solution approaches

The background and the literature in liner fleet scheduling is reviewed and the objectives and assumptions of our approach are explained. We develop a detailed and realistic model for the estimation of the operating costs of liner ships on various routes, and present a linear programming formulation for the liner fleet deployment problem. Independent approaches for fixing both the service frequencies in the different routes and the speeds of the ships, are presented.     

Fleet deployment optimization for liner shipping Part 2. Implementation and results

We use linear programming (LP) for solving the problem of the optimal deployment of an existing fleet of multipurpose or fully containerized ships, among a given set of routes, including information for lay-up time, if any, and type and number of extra ships to charter, based on a detailed and realistic model for the calculation of the operating costs of all the ship types in every route and on a suitable LP formulation developed in earlier work of the authors. The optimization model is also applicable to the problem of finding the best fleet compostion and deployment, in a given set of trade routes, which may be the case when a shipping company is considering new or modified services, or a renewal of the existing fleet. In addition, two promising mixed linear-integer programming formulations are suggested.     

Réflexions sur le transfert méthodologique de l’analyse qualitative d’accidents de la circulation routière issue de l’étude détaillée des accidents (EDA) fran?aise aux procédures d’accidents colombiennes

Nearly 90% of the traffic accidents that occur worldwide happen in developing countries. Yet road safety remains a little-studied subject in these countries, and notably accidentology studies, which provide a wealth of information. One of the major problems in studying road accidents in developing countries lies in the lack of reliable accident data. Indeed, while the comprehensive accident analysis methodologies used in developed countries provide an understanding of the origin of accidents and accident processes, as well as making it possible to define suitable, effective actions, they require reliable and relatively detailed accident data. These methodologies are notably based on detailed accident studies (DASs) and their adaptation to the analysis of accident reports. Colombia has an infrastructure for gathering and storing traffic accident data that can be used to perform comprehensive accident analyses. This article defines the feasibility of a technology transfer (clinical accident analysis) to the Colombian equivalent of accident reports. These observations are part of a doctoral thesis prepared jointly by the IFSTTAR Accident Mechanisms Research Unit and the University of the Andes in Bogotá.     

Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

ABSTRACT

This study provides a bibliometric review of 279 studies on the applications of big data and artificial intelligence (AI) in the maritime industry, published in 214 academic outlets, authored by 842 scholars. We extracted bibliographical data from the Web of Science database and analysed it using the Bibliometrix tool in R software. Based on citation analysis metrics, we revealed the most influential articles, journals, authors and institutions. Using the bibliographic coupling methodology, we identified four underlying research clusters: (1) digital transformation in maritime industry, (2) applications of big data from AIS, (3) energy efficiency and (4) predictive analytics. We analysed these clusters in detail and extracted future research questions. Besides, we present research collaboration networks on the institution and author level.