Search results

The total capacity of ambulances in metropolitan cities is often less than the post-disaster demand, especially in the case of disasters such as earthquakes. However, because earthquakes are a rare occurrence in these cities, it is unreasonable to maintain the ambulance capacity at a higher level than usual. Therefore, the effective use of ambulances is critical in saving human lives during such disasters. Thus, this paper aims to provide a method for determining how to transport the maximum number of disaster victims to hospitals on time.

The transportation-related disaster management problem is complex and dynamic. The practical solution needs decomposition and a fast algorithm for determining the next mission of a vehicle. The suggested method is a synthesis of mathematical modeling, scheduling theory, heuristic methods and the Voronoi diagram of geometry. This study presents new elements for the treatment, including new mathematical theorems and algorithms. In the proposed method, each hospital is responsible for a region determined by the Voronoi diagram. The region may change if a hospital becomes full. The ambulance vehicles work for hospitals. For every patient, there is an estimated deadline by which the person must reach the hospital to survive. The second part of the concept is the way of scheduling the vehicles. The objective is to transport the maximum number of patients on time. In terms of scheduling theory, this is a problem whose objective function is to minimize the sum of the unit penalties.

The Voronoi diagram can be effectively used for decomposing the complex problem. The mathematical model of transportation to one hospital is the P‖ΣU_j problem of scheduling theory. This study provides a new mathematical theorem to describe the structure of an algorithm that provides the optimal solution. This study introduces the notion of the partial oracle. This algorithmic tool helps to elaborate heuristic methods, which provide approximations to the precise method. The realization of the partial oracle with constructive elements and elements proves the nonexistence of any solution. This paper contains case studies of three hospitals in Tehran. The results are close to the best possible results that can be achieved. However, obtaining the optimal solution requires a long CPU time, even in the nondynamic case, because the problem P‖ΣU_j is NP-complete.

This research suggests good approximation because of the complexity of the problem. Researchers are encouraged to test the proposed propositions further. In addition, the problem in the dynamic environment needs more attention.

If a large-scale earthquake can be expected in a city, the city authorities should have a central control system of ambulances. This study presents a simple and efficient method for the post-disaster transport problem and decision-making. The security of the city can be improved by purchasing ambulances and using the proposed method to boost the effectiveness of post-disaster relief.

The population will be safer and more secure if the recommended measures are realized. The measures are important for any city situated in a region where the outbreak of a major earthquake is possible at any moment.

This paper fulfills an identified need to study the operations related to the transport of seriously injured people using emergency vehicles in the post-disaster period in an efficient way.

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.

This paper presents a generic simulation model to determine the equipment mix (quay, yard and intra-terminal transfer) for a Container Terminal Logistics Operations System (CTLOS). The simulation model for the CTLOS, a typical type of discrete event dynamic system (DEDS), consists of three sub-models: ship queue, loading-unloading operations and yard-gate operations. The simulation model is empirically applied to phase 1 of the Yangshan Deep Water Port in Shanghai. This study considers different scenarios in terms of container throughput levels, equipment utilization rates, and operational bottlenecks, and presents a sensitivity analysis to evaluate and choose reasonable equipment ratio ranges under different operational conditions.

The purpose of this paper is to investigate empirically how information and communication technologies (ICT) can contribute to reduction of CO₂ emissions in road freight transport and to identify opportunities for further improvements.

This research adopts a multiple case study approach with three leading UK grocery retailers as exemplars of fast-moving consumer goods retailers, conducted using multiple data collection techniques including interviews, system demonstrations, onsite observations and the use of archive information.

ICT solutions have a direct positive impact on CO₂ emissions reduction but opportunities to further reduce CO₂ emissions are perceived as lying beyond retailers’ own distribution networks. These opportunities are not fully utilised due to the complexities of collaborative ICT provisions and retailers’ reluctance to share information with competitors.

A limitation of the study is that it is exploratory and only three cases were examined. Even though these three retailers represent over 60 per cent of the UK grocery retail sector, other retailers may deploy significantly different ICT applications.

The research provides an overarching insight for businesses on how to leverage the existing and emerging information technologies for environmental and economic benefits.

While sustainability issues have received increasing attention recently, the role of ICT in freight transport for CO₂ emissions reduction has not been investigated in depth and its impact is largely unknown. This research advances understanding about how ICT contributes CO₂ emissions reductions and provides a framework for further investigation.

The purpose of this paper is to optimize the design of charging station deployed at the terminal station for electric transit, with explicit consideration of heterogenous charging modes.

The authors proposed a bi-level model to optimize the decision-making at both tactical and operational levels simultaneously. Specifically, at the operational level (i.e. lower level), the service schedule and recharging plan of electric buses are optimized under specific design of charging station. The objective of lower-level model is to minimize total daily operational cost. This model is solved by a tailored column generation-based heuristic algorithm. At the tactical level (i.e. upper level), the design of charging station is optimized based upon the results obtained at the lower level. A tabu search algorithm is proposed subsequently to solve the upper-level model.

This study conducted numerical cases to validate the applicability of the proposed model. Some managerial insights stemmed from numerical case studies are revealed and discussed, which can help transit agencies design charging station scientifically.

The joint consideration of heterogeneous charging modes in charging station would further lower the operational cost of electric transit and speed up the market penetration of battery electric buses.

For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.

The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.

By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.

Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.

The purpose of this paper is to review the relevant literature in order to identify trends and suggest some possible directions for future research in the framework of humanitarian aid distribution logistics with accessibility constraints.

The authors developed a systematic literature review to study the state of the art on distribution logistics considering accessibility constraints. The electronic databases used were Web of science, Scopus, Science Direct, Jstor, Emerald, EBSCO, Scielo and Redalyc. As a result, 49 articles were reviewed in detail.

This study identified some gaps, as well as some research opportunities. The main conclusions are the need for further studies on the interrelationships and hierarchies of multiple actors, explore intermodality, transshipment options and redistribution relief goods to avoid severe shortages in some nodes and excess inventory in others, studies of the vulnerability of transport networks, correlational analysis of road failures and other future lines.

The bibliography is limited to peer-reviewed academic journals due to their academic relevance, accessibility and ease of searching. Most of the studies included in the review were conducted in high-income countries, which may limit the generalizability of the results to low-income countries. However, the authors focused on databases covering important journals on humanitarian logistics.

This paper contextualises and synthesises research into humanitarian aid distribution logistics with accessibility constrains, highlights key themes and suggests areas for further research.

This paper aims to optimize the charging schedule for battery electric buses (BEBs) to minimize the charging cost considering the time-of-use electricity price.

The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model. The objective is to minimize the total charging cost of the BEB fleet. The charge decision of each BEB at the end of each trip is to be determined. Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule.

This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line. The results show that the total charge cost with the optimized charging schedule is 15.56% lower than the actual total charge cost under given conditions. The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent, which can provide a reference for planning the number of charging piles.

Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.

The purpose of this paper is to develop an original model and a solution procedure for solving jointly three main strategic fleet management problems (fleet composition, replacement and make-or-buy), taking into account interdependencies between them.

The three main strategic fleet management problems were analyzed in detail to identify interdependencies between them, mathematically modeled in terms of integer nonlinear programing (INLP) and solved using evolutionary based method of a solver compatible with a spreadsheet.

There are no optimization methods combining the analyzed problems, but it is possible to mathematically model them jointly and solve together using a solver compatible with a spreadsheet obtaining a solution/fleet management strategy answering the questions: Keep currently exploited vehicles in a fleet or remove them? If keep, how often to replace them? If remove then when? How many perspective/new vehicles, of what types, brand new or used ones and when should be put into a fleet? The relatively large scale instance of problem (50 vehicles) was solved based on a real-life data. The obtained results occurred to be better/cheaper by 10% than the two reference solutions – random and do-nothing ones.

The methodology of developing optimal fleet management strategy by solving jointly three main strategic fleet management problems is proposed allowing for the reduction of the fleet exploitation costs by adjusting fleet size, types of exploited vehicles and their exploitation periods.

The optimisation of forest fuels supply chain involves several entities actors, and particularities. To successfully manage these supply chains, efficient tools must be devised with the ability to deal with stakeholders dynamic interactions and to optimize the supply chain performance as a whole while being stable and robust, even in the presence of uncertainties. This work proposes a framework to coordinate different planning levels and event-based models to manage the forest-based supply chain. In particular, with the new methodology, the resilience and flexibility of the biomass supply chain is increased through a closed-loop system based on the system forecasts provided by a discrete-event model. The developed event-based predictive model will be described in detail, explaining its link with the remaining elements. The implemented models and their links within the proposed framework are presented in a case study in Finland and results are shown to illustrate the advantage of the proposed architecture.