Journals in Decision sciences and transportation
Journals in Decision sciences and transportation
- ISSN: 2210-9706
Journal of Rail Transport Planning & Management
Affiliated with the International Association of Railway Operations ResearchJournal of Rail Transport Planning & Management aims to stimulate the quality of service for railway passengers and freight customers by improving the knowledge on effectiveness and efficiency of capacity management, timetabling, management and safety of railway operations. It covers the whole range of light rail, metro, heavy and high-speed railway systems. The journal will create a platform for regular transfer of knowledge, new tools and discussion of innovative contributions regarding the analysis of passenger and freight railway transport, estimation of traffic demand and capacity, design of timetables, scheduling of trains and crews, dispatching, signalling, train control, automatic train operation, optimal use of rolling stock and energy in order to increase the efficiency and competitiveness of passenger and freight transport.The journal presents innovative theoretical approaches, high-tech concepts, new technological, financing and business management models and tools that can provide higher flexibility, performance and punctuality of trains operating on dedicated lines and in heterogeneous networks. Journal of Rail Transport Planning & Management integrates the expertise from different scientific disciplines as physical planning, transport modelling, traffic analysis, (system) engineering, mathematics, physics, computer science, economics and (transport) policy analysis.The articles accepted comprise generic theoretical research projects, original concise transport and business plans, pilot technical and economic feasibility analyses, as well as genuine impact assessment studies in the railway domain.Journal of Rail Transport Planning & Management supports the development of a “Network of Excellence” in the field of railway system planning, operations research, business development, traffic control and operations management. It brings together academics and professionals who advise governments, railway infrastructure managers, train operating companies and industrial suppliers on promising and successful innovation strategies for railway transport policy, lines, networks, operations and management.
- ISSN: 1366-5545
Transportation Research Part E: Logistics and Transportation Review
Transportation Research Part E: Logistics and Transportation Review (TR-E) is differentiated from its sister journals (TR-A, TR-B, TR-C, TR-D, and TR-F). As reflected in their title, the commonality between these journals is the focus on ‘Transportation,’ but TR-E is differentiated by specializing in ‘Logistics.’ Of course, it is widely accepted that transportation is undoubtedly one of the most critical components of logistics. TR-E publishes informative and high-quality articles drawn from across the spectrum of logistics components. The related research studies are multi-disciplinary and include (i) hard/ classic logistics research, such as transportation, material handling, packaging, warehousing, inventory, and handling, and so on (ii) soft logistics research by adding Operations Management (OM) and Supply Chain Management (SCM) concepts, tools, and philosophies to the classic logistics, such as sustainability, risk and disruption, circular economy, and artificial intelligence.There are no limitations to the research methods utilized. Therefore, various research methods can be used, such as analytical (e.g., operations research techniques including game theory, queuing theory, dynamic programming, linear, integer, and nonlinear programming), quantitative and qualitative empirical research (e.g., time series, regression, microeconomics), simulation, mixed research methods (e.g., combining surveys and case studies with quantitative data analysis), experimental research (e.g., controlled experiments, lab experiments, and field experiments), case studies (e.g., in-depth analysis), machine learning, artificial intelligence and network analysis (e.g., graph theoretic concept).