Fleet Type Research Articles

Heterogeneous Fleet Green Vehicle Routing Problem: A Literature Review

Transportation, as a part of the supply chain process, contributes to carbon emission which leads to climate change and global warming. This environmental issue gives an impact to decisions regarding the supply chain of a company. One way to deal with this issue is by analyzing their vehicle routing problem. In this study, the issue about routing problems in green supply chain by considering the heterogeneous fleet is being discussed. One variant of Green Vehicle Routing Problem (GVRP) reviewed in this paper is about Heterogeneous Alternative Fuel Vehicles for Green Vehicle Routing Problem (HAFVGVRP). The purpose of this study is to review the development of GVRP with heterogeneous alternative fuel vehicles and the gap or state-of-the-art on existing researches. The review was classified according to the objectives, type of fleet, and solution used. Moreover, this study also presents the trend and direction of further research.

Penerapan Metode Topsis Dalam Pemilihan Jasa Ekspedisi

Many factors influence the selection of expedition services, such as the length of delivery, the price offered to the services provided. At first the company chose the expedition service partner based solely on customs, but often there were obstacles such as unsatisfactory service, less neat packing of goods, high prices and so forth. The impact is the customer's disappointment with the service we provide.In selecting the best expedition services, a mechanism is needed to deliver the goods that are truly feasible. One of them can be done by using a decision support system with the topsis method. Where the TOPSIS method has a simple and easy-to-understand concept and has the ability to measure the relative performance of decision alternatives in a simple mathematical form. The criteria used in this study include price, service, delivery time, range, type of fleet and company experience, while alternative options for expedition services are Ezra Cargo, Sentral Cargo, Dakota Cargo, Indah Logistik Cargo, Run Logistics, Trans Java Sumatra. The results of calculations using the Topsis method can be said that, the selection of the best expeditionary services is Central Cargo with first place with a value of 0,8887, then followed by Indah Logistik Cargo with second place with a value of 0,5866, and third place is Ezra Cargo with a value of 0,5444. Thus, Central Cargo is the best solution in the selection of expedition services at PT. Tachimita Hoka Utama.

INCEPTS: Software for high-fidelity electric vehicle en route state of charge estimation, fleet analysis and charger deployment

As the electrification of the transportation industry and growing adoption of these electric vehicles continues, the demand for charging infrastructure is increasing concurrently. Properly deploying this infrastructure requires that there exist models which can adequately estimate the performance of these vehicles under real scenarios. While there has been significant work on estimating energy-consumption for realistic drive profiles, there is a need to systematically incorporate the conditions (e.g. wind, elevation) along a route for enabling efficient charger deployment. In this work, we have developed a software package known as INCEPTS, an agent-based simulation software that can predict high-fidelity electric vehicle performance and can capture the dynamics exhibited by the individual vehicles as they travel on their respective routes. The software then uses this to analyze fleets of vehicles which will provide the fleet performance statistics that result from various impacts exhibited by the fleet in the simulated area. These statistics can then be further used to inform decisions such as charger deployment to ensure that the placement of chargers adapts to the local needs of the electric vehicle fleet. Furthermore, this software is developed such that it is capable of simulating different kinds of electric vehicles (e.g. cars, trucks, eVTOLs) and different locations. To demonstrate the capabilities of the software, a variety of simulations are performed using Massachusetts as a target location. The first set of simulations show the importance of accounting for local conditions of individual vehicles. For example, the difference is state-of-charge could differ by up to 30% for the same distance traveled. The second set of simulations looked at the fleet performance within Massachusetts in which a bimodality of energy used per mile is observed, with means at 184 Wh/mi and 244 Wh/mi. Our work demonstrated that this bimodality results from a combination of both local conditions and geometric restrictions caused by the road network. These results are indicative of the unique capabilities of the INCEPTS platform and we plan to demonstrate additional use-cases in follow-up studies. • Coupling of environmental factors with models for battery, vehicle and fleet dynamics. • Scalable vehicle simulations for fleet statistics and complex systems analysis. • The software can simulate any type of electric vehicle fleet in any part of the world. • Massachusetts, U.S. case study used to demonstrate the software’s capabilities.

Incorporating Maintenance Infeasibilities in an Aircraft Rotation Planning Model

In any airline’s schedule development process, aircraft rotations must be planned for individual fleet types after fleet assignment. The aircraft rotation plans must conform to stringent maintenance requirements and this problem can be formulated as a periodic routing problem on an Eulerian graph. We analyze the computational complexity of developing maintenance rotations when some overnighting aircraft may not have sufficient time on the ground to complete extended maintenance (referred to as a maintenance infeasibility). The paper also provides a theoretical analysis of heuristics for the aircraft maintenance rotation problem with maintenance infeasibilities.

COVID-19 Pandemic as a Mechanism of the Motion of an Aircraft in MIRCE Mechanics

The COVID-19 outbreak has shown that pandemics, like other rarely occurring natural catastrophes, have happened in the past and will happen in the future. Although humans cannot prevent dangerous viruses from emerging, they should be prepared to dampen their consequences for the economy and all of society. The main objective of this paper is to address the COVID-19 pandemic as a novel mechanism of the motion of an aircraft in MIRCE Mechanics, as only then the most effective technological, social and economic actions can be taken by humans to deal with it. Examples of devastating impacts on aviation world-wide are given in the paper, based on available statistics provided by governmental and global commercial aviation associations. Also, examples of professional and technological solutions taken to cushion the impact of COVID-19 on safety in aviation are presented. To assist airlines in the selection process of aircraft types that should be returned to the post pandemic service MIRCE Function ability and Profitability Equations are presented in the paper. However, they are applicable only when the mechanisms of the motion of an industrial system through MIRCE Space are known. As COVID-19 pandemic was not known until the beginning of 2020 business plans of airlines world-wide are for several orders of magnitude off the target, measured in flying hours delivered, revenue generated, an unprecedented number of aircraft grounded and prematurely retirement of B747 and A380 aircraft type from active service. Thus, this paper is bringing together the physiological side of COVID-19 and its physical impact on the operational side of airlines in order to assist them to predict the expected positive and negative work by each aircraft type grounded. This analysis will guide them to decide what type of fleet they should have in the post pandemic times and thus secure the business existence.

The Tail Assignment Problem: A Case Study at Vueling Airlines

To schedule aircraft, assignments of fleet types to flights and of aircraft to routes must be determined. The former is known as the fleet assignment problem while the latter is known as the aircraft routing problem in the literature. Aircraft routing is usually addressed as a feasibility problem whose solution is needed for constructing crew schedules. These problems are usually solved from 4 to 6 months before the day of operations. Therefore, there is limited information regarding each aircraft’s operational condition. The tail assignment problem, which has received limited attention in air transportation literature, is solved when additional information regarding operational conditions is revealed aiming at determining each aircraft’s route for the day of operations accounting for the originally planned aircraft routes and crew schedules. Therefore, it is a problem to be solved the day before operations. We propose a mathematical programming approach based on sequencing that captures all operational constraints and maintenance requirements while assignment costs are minimized. Computational experiments are based on realistic cases drawn from a Spanish airline, which features a network with more than 1000 flights and more than 100 aircraft.

A Novel Approach to the Tail Assignment Problem in Airline Planning

Combinatorial optimization problems abound in the field of airline planning. Aircraft and passengers fly on networks made up of flights and airports. To schedule aircraft, assignments of fleet types to flights and of aircraft to routes must be determined. The former is known as the fleet assignment problem while the latter is known as the aircraft routing problem in the literature. Aircraft routing is typically addressed as a feasibility problem, the solution to which is required for the construction of crew schedules. All these issues are typically resolved 4 to 6 months before the day of operations. As a result, there is little information available about each aircraft’s operational status when making such decisions. The tail assignment problem is solved when additional information about operational conditions is revealed, with the goal of determining each aircraft’s route for the day of operations while accounting for the planned aircraft routes and crew schedules. It is a problem that must be resolved close to the day of operations. We propose a mathematical programming approach that captures all operational constraints and maintenance requirements while minimizing operational costs and schedule changes relative to original plans. The computational experiments are based on realistic cases drawn from a Spanish airline with over 1000 flights and over 100 aircraft.

Integrated scheduling of suppliers and multi-project activities for green construction supply chains under uncertainty

The green construction supply chain is one of the topics that have been recently discussed in relation to supply chain fundamentals, especially in the construction supply chain. Specifically, a project network consisting of several concurrent projects is managed with the aim of not only minimizing delays in all projects, but also simultaneously minimizing the logistical costs, e.g., procurement, ordering, and transportation costs, and pollution levels of vehicles. Although these projects operate independently, they are affected by common suppliers and final quality inspection by the common committee, thus requiring consistent project review. This study evaluates the construction supply chain using a mathematical model of bi-objective linear programming. To realize this objective, the actual environmental impacts of vehicles in terms of distance, pollution rate, and slope of the road are considered. This paper also discusses the synergy between supplier selection and project planning and scheduling in the proposed green supply chain. In addition, the issues of balancing the supplier selection, choosing the type of fleet, and project time planning, which has become a real operational challenge in the construction industry, are also investigated in the paper such that by minimizing the project delays, logistical costs and the propagation of greenhouse gases can be minimized as well. Moreover, in order to make the results more realistic, the levels of production capacity and costs are considered in an uncertain (fuzzy-probabilistic) environment under three economic conditions, i.e., pessimistic, normal, and optimistic.

Environment-Friendly School Bus Routing Problem With Heterogeneous Fleet: A Large-Scale Real Case

In the present study, we concentrate on the formulation and the exact solution of a specific vehicle routing problem with environmental concerns, which is a complex actual problem of staff service bus route planning for a university in a metropolitan city. Taking into account the air pollution related measures for representing the cost of environmental concerns in addition to the vehicle rental and fuel consumption related operational costs, we formulate a flow-based mixed integer linear program for the environment-friendly school bus routing problem specific to both homogeneous and heterogeneous vehicle fleets. We provide exact solutions to the instance sets we have designed specific to variants of the problem considering the fleet type, vehicle capacity, and maximum route length. Results from model based exact solutions for our formulations show up to 30% of reduction in the overall cost for the heterogeneous fleet case when compared to the homogeneous ones, and suggest a routing plan that enables the utilization of almost the entire capacity of all the buses assigned. We discuss in details the trade-offs between the cost items, travel times, and travel distances in composing a vehicle fleet considering the demand sprawled over the metropolitan area.

Tactical and operational planning for socially responsible fresh agricultural supply chain

Addressing an integrated decision-making structure for planting and harvesting scheduling may lead to more realistic, accurate, and efficient decision in fresh product supply chain. This study aims to develop an integrated bi-objective tactical and operational planning model for producing and distributing fresh crops. The first objective of the model is to maximize total revenue of supply chain. Over the past few years, there has been a considerable shift in emphasis in social responsibility of supply chains. Therefore, a key purpose of this article is to plan a socially responsible fresh agricultural supply chain as the second objective function. The proposed bi-objective model seeks to make optimal decisions on planting, harvesting scheduling (harvesting pattern), selecting the transport fleet type, and products supply channel to the consumers. To conduct the analysis, numerical examples are provided based on a real case study and the true Pareto front is achieved with augmented e-constraint method. The results indicated the applicability of the proposed model and verified its validity. Moreover, comparison between total weighting and e-constraint method is provided to ensure the efficiency of Pareto solutions.

Analysis of Drone Fleet Type and Quantity for Medical Package Distribution in Emergency System

In order to cope with the disasters caused by the worst hurricane in Puerto Rico in 2017, it is necessary to build an emergency system to reduce the losses. An emergency system should include the location of ISO standard dry cargo containers and the distribution of emergency medical packages. This paper discusses the distribution of emergency medical package. Based on the above location results of ISO standard dry cargo container, taking the demand of disaster areas not exceed its supply into consideration and considering the timeliness and weak economy, a multi-objective mixed integer programming model is constructed on the premise of minimum transportation time and cost. It is determined that the drone fleet consists of four B, one C and one F drones. Through the optimization model, the distribution plan of emergency medical packages is formulated.

An agent-based simulation framework for the study of urban delivery

In recent years, cities and especially urban mobility have undergone remarkable changes. Significant advances in technology have been translated into new mobility services for both goods and people. One evident change has been the transformation of traditional vehicle fleets into more open fleets, in the sense that their members can proactively decide whether or not they are part of a certain fleet and whether or not they perform certain services. Fleets of this type make the decision-making process to be highly distributed, and rule out some of the typically centralized decisions. The management and control of this type of open fleets is severely more complex and, for this reason, the availability of simulation tools that allow for their analysis can be very useful. In accordance with this, the main contribution of this work is the development of an agent-based simulation tool specifically designed for the simulation of new urban mobility models. In this way, the tool can simulate any type of fleet in different urban scenarios, including a solution of the Last Mile Delivery problem, which is also included as a proof of concept in this paper.

STATE OF FAMILY FUNCTIONING OF LONG-DISTANCE SAILORS OF DIFFERENT SOCIAL GROUPS AND LEVELS OF PSYCHO-SOCIAL STRESS

The aim of the study was to investigate the relationship between the severity of family anxiety as an indicator of family functioning and the level of psychosocial stress (PS) in long-distance sailors, to determine further targets of personalized mental health measures for this contingent. Contingent and research methods. During 2016-2019, 110 officers of the command staff of the Maritime Merchant Navy, 90 sailors of the Maritime Merchant Fleet, 70 representatives of the command unit of the Maritime Passenger Fleet and 30 privates of the Maritime Passenger Fleet were surveyed. All were examined by men, citizens of Ukraine. The study included the use of clinical-psychopathological and psychodiagnostic methods. The study revealed differences in the manifestations of family guilt, family tension and family anxiety in the command staff and sailors of the merchant and passenger fleets. The greatest influence on the intensity of family anxiety was exerted by the level of PS: at low levels of stress the indicators of family anxiety (including its individual components) were the lowest, and at severe stress the indicators of family anxiety were the highest. The basis of «family anxiety», as a rule, was the poorly perceived insecurity of the sailor in some very important aspect of family life (for example, insecurity in the feelings of his wife to himself, or insecurity). Often such worries, contrary to self-image, were supplanted, which led to anxiety in family relationships. An important component of «family anxiety» was the feeling of helplessness and inability to interfere in the course of events in the family, in order to direct them in the desired direction. Sailors with «family anxiety» did not feel like a significant actor in the family (despite the real warming of an important position and active role in the family). The influence of social group (command staff or sailors) and the type of fleet (commercial or passenger) on the level of family anxiety, family guilt and family tensions was secondary. Keywords: long-distance sailors, psychosocial stress, family anxiety, family functioning.

Guide to multi-objective optimization for the green vehicle routing problem

This article aims to present research conducted on the literature regarding Multi-objective Optimization (MOO) for routing problems with environmental considerations (EC), referred to here as Multi-objective Optimization for the Green Vehicle Routing Problem (MOOGVRP). A Brazilian database, CAPES (Coordination for the Improvement of Higher Education Personnel), was used to collect articles of general application, case studies and reviews in English starting from, since 2012. The terms “green vehicle routing problem” (GVRP), “pollution routing problem” (PRP), “vehicle routing problem in reverse logistics” (VRPRL) and “multi-objective” were used in the research protocol. Consequently, this study obtained 1,744 research results that, following the application of the filtering criterion, resulted in a sample of 76 articles from 38 journals, for which a bibliometric data (bibliometric review) survey was conducted. When dealing with the bibliometric data of the sample, it was possible to identify information such as the number of publications per year and types of published works. Information was also identified regarding the most frequently used journals and the countries and institutions that published the most articles on the proposed theme. It was also possible to analyze the frequency of the protocol terms in the title, abstracts and keywords, the relationship between taxonomies, vehicle fleet types, multi-objective procedures, and VRP procedures. Information was also found regarding solution procedures, number of objectives, and programming languages for computational implementation, the frequency of the most used objectives, and the most cited articles in the sample. The originality of this article lies in how the research is presented, highlighting the results and particular details obtained through the survey, which may be considered of great academic importance in the sense of guiding the trends for future research.

Choice-Based Airline Schedule Design and Fleet Assignment: A Decomposition Approach

We study an integrated airline schedule design and fleet assignment model for constructing schedules by simultaneously selecting from a pool of optional flights and assigning fleet types to these scheduled flights. This is a crucial tactical decision which greatly influences airline profit. As passenger demand is often substitutable among available fare products between the same origin-destination pair, we study an optimization model that integrates within it a passenger choice model for fare product selections. To tackle the formidable computational challenge of solving this large-scale network design problem, we propose a decomposition approach based on partitioning the flight network into smaller subnetworks by exploiting weak dependency in the network structure. The decomposition relies on a series of approximation analyses and a novel fare split problem to reliably measure the approximation quality introduced by the partition by optimally allocating fares of products shared by flights in different subnetworks. We present several reformulations by representing fleet assignment and schedule decisions using composite variables and formally characterize the relationship of their strengths. This gives rise to a new reformulation that is able to flexibly trade off strength and size. We conduct detailed computational experiments using two realistically sized airline instances to demonstrate the effectiveness of our approach. Under a simulated passenger booking environment with both perfect and imperfect forecasts, we show that the fleeting and scheduling decisions informed by our approach deliver significant and robust profit improvement over benchmark implementations and previous models in the literature.

A Strategic Multistage Tactical Two-Stage Stochastic Optimization Model for the Airline Fleet Management Problem.

This work proposes stochastic optimization for the airline fleet management problem, considering uncertainty in the demand, operational costs, and fares. In particular, a multistage tree is proposed, compounded of strategic and tactical nodes. At the former ones, fleet composition decisions are made, while at the latter ones, aircraft assignment decisions are formulated. Computational experiments are based on a small air network with seven strategic nodes and fourteen tactical nodes (i.e., seasons) where two fleet types are available to be included: Airbus 320, and Boeing 737. These results provide the optimal fleet planning and assignment at both strategic and tactical scopes. Finally, it is shown the superior performance of the stochastic version of this problem against the deterministic one.

Models for aircraft maintenance routing problem with consideration of remaining time and robustness

Aircraft maintenance routing problem is especially important with respect to timing and costs for an airline company. This work establishes an integer linear programming (ILP) model (Model I) for aircraft maintenance routing problem with the objective to minimize the number of aircrafts and total remaining flying time. Then, we extend the Model I to Model II and Model III, respectively. In the Model II, we consider the robustness based on aircraft delay probability, and add the robust constrains to the model aiming at reducing total aircraft delay costs. For the Model III, we take into account the fleet type of the aircrafts, whose objective is to minimize the total flying cost. In terms of solution method, we improve a heuristic of the variable neighborhood search (VNS) algorithm to solve the Model I and Model II which can generate a suboptimal solution quickly in reasonable time. In order to verify the effectiveness of the heuristic algorithm, the experimental results are compared with the commercial software solver CPLEX. The experimental results on real world flight network show that the performance of the heuristic algorithm is much better than CPLEX in terms of the computation efficiency for large scale test instance. Moreover, the heuristic algorithm also can obtain high quality solutions.

Size distributions and size-segregated chemical profiles of particulate matter in a traffic tunnel of East-Central China

Size distributions for number and mass concentrations, size-segregated chemical compositions and chemical profiles of particulate matter (PM) were determined at two sampling sites (SP1 and SP2) in a traffic tunnel of East-Central China. Particle size distributions of number concentration presented single large peaks at 6–17 nm and inconspicuous peaks around 100 nm on each day, with peak phenomenon in line with rush hours. Particle mass distributions showed high concentrations with particle diameters in the last stage (6800–10000 nm). For size-segregated particles, PM mass concentration in 1.1–2.1 μm was found to be high, and particles smaller than 2.1 μm (PM2.1) accounted for 43% (SP1) and 37% (SP2) of particles smaller than 10 μm (PM10). PM in 3.3–4.7 μm size range was also high for SP2 (accounting for 15% of PM10). High organic carbon (OC), NH4+, K+, Cl−, NO3−, and SO42− concentration were observed in PM2.1, and Mg2+, Ca2+, and F− in size range of 2.1–10 μm was high. For fine particle (PM2.5) profiles, average mass concentrations of PM2.5 were 199 ± 63 and 247 ± 45 μg m−3 for SP1 and SP2. OC was the highest constituent, followed by SO42− and then NO3− for SP2, while SO42− and NO3− were higher than OC for SP1. OC and elemental carbon (EC) concentrations for SP2 were higher than those for SP1. Comparing to other tunnel studies, PM2.5 mass concentration at SP2 was similar to that of Shing Mun Tunnel, but 6 and 4 times higher than those of Loma Larga Tunnel and Chung-Liao Tunnel. OC proportion in this study was approximately 0.5, 0.2 and 1 times relative to those in other three tunnels, and EC was 0.1, 0.4 and 0.2 times relative to those in other tunnels, which depended on traffic fleet and vehicle types. The crustal elements in this tunnel showed higher content than those in other tunnels, illustrating the local differences.

Analysis of the Costs of Selected Car-sharing Services - a Case Study on Six Continents Analysis of the Costs of Selected Car-sharing Services - a Case Study on Six Continents

Different types of transport solutions that are to influence the sustainability of urban logistics are increasingly used around the world. The same applies to the opportunities offered by the implementation of shared mobility services. According to this idea, car-sharing systems are currently present on six continents of the world and it is anticipated that by 2025 there will be over 36 million users worldwide sharing car-sharing services. In line with this trend, it is worth paying attention to aspects that will encourage the public to use car-sharing services. Because the price is one of the main factors for the society during making a decision about using car-sharing services, the author decided to analyze the costs of car-sharing mobility. In the text basic assumptions about car-sharing services and their development were presented. Then, the article showed the analysis of the cost of using services on six continents in the line of temporary and parking fees. In addition, the work also refers to the impact of the type of vehicle fleet on the price level. The aim of the work was to assess the occurrence of differences between the services offered and the relation between costs and the assumptions of sustainable transport development.

Cost structure and financial performance of marine commercial fisheries in the South Brazil Bight

In Brazil, economic data on fisheries are generally scarce, and difficult to interpret with respect to costs and fishery viability, thus making it difficult to practice consistent policy and industrial decision-making. Financial performance was assessed, as were the key factors affecting the fishing costs and profitability of the major fisheries fleets that operated in three Southeast and South regions. Through an unprecedented set of field survey data from 160 fishing vessels obtained during 2013–2014, we provide a cost-benefit comparison between different fleets and landing sites. Three generalized additive models (GAMLSS) were explored to identify major factors affecting gross profit. Fuel consumption, vessel repairs, revenue, and volume of catch were the most statistically significant factors explaining gross profit margin. For trawlers and purse-seiners, technical features such as vessel size and the number of fishing trips explained profitability, respectively, while the landing costs were significant to both types of fleet. Gross profits for trawlers also depend on ice cost and fleet type. Large pelagic fisheries showed the highest gross profit, while shrimp-trawlers, bottom-gillnetters and a purse-seining fleet showed the lowest profit, close to unviability. Indirectly, population size of target species may be influencing profitability. Labor wages increase when the financial performance of fleets improve; however, reduced yields and high operational cost levels may decrease the salaries. Specific policy advice and management strategies aiming to protect both financial performance and natural resources are highlighted, including the importance of cost-benefit analysis to help businessmen and vessel owners to identify factors that influence fleet profitability, thereby facilitating the creation of measures for increased efficiency. The approach presented may contribute to standardizing economic knowledge construction in data-poor fisheries, such as S/SE Brazil’s and in other jurisdictions of Brazil or elsewhere.