Determination Of Fleet Size Research Articles

Expected service dimensions and service levels for paratransit considering future mobility needs in emerging countries

• Mobility-as-a-Service (MaaS) promises improved modal efficiency and integration among public transit and flexible paratransit services (FPS). • Key service dimensions and issues of flexible paratransit services are analysed in the context of MaaS. • Expected service level for these service dimensions are determined using the level of service (LOS) approach based on user perception. • Ride matching as per expected waiting time and service hours via MaaS agencies would ensure proper demand-supply match and fleet size determination. In emerging countries, flexible transport systems (FTS) are mostly informal and are provided by individual paratransit operators/drivers. These services are largely unregulated thus resulting in uncoordinated operations with poor service quality. Earnings and working conditions of paratransit drivers/operators are also poor due to loosely regulated fleet size and other operational and regulatory issues which results in further deterioration of service quality. This research identifies key service dimensions and issues of paratransit services and also determines the expected service level for these service dimensions using the level of service approach based on user perception. LOS scales are designed for different service attributes using a five-point satisfaction and importance rating system. For quantitative attributes, five-level LOS scales are determined by applying the Law of Successive Interval Scaling, whereas for qualitative attributes, the same has been developed using the frequency of response for each level of importance for each sub-attribute. Subsequently, we explore various policies and regulatory measures towards reform and redesign of paratransit services and other mobility needs. Operator profitability can be achieved both through the controlled entry of operators through the issue of permits and/or by relaxing the current service level of some service aspects which are at LOS B level of service. The LOS scales can help in future service design of paratransit services in emerging countries which can offer an affordable alternative to ridesourcing and ride-sharing using cars. The study is conducted in two medium-sized cities in India namely Rajkot and Vishakapatnam.

Bi-objective green in-house transportation scheduling and fleet size determination in mixed-model assembly lines with mobile robots

PurposeFacing the challenge of increasing energy cost and requirement of reducing the emissions, identifying the potential factors of them in the manufacturing factories is an important prerequisite to control energy consumption. This paper aims to present a bi-objective green in-house transportation scheduling and fleet size determination problem (BOGIHTS&FSDP) in automobile assembly line to schedule the material delivery tasks, which jointly take the energy consumption into consideration as well.Design/methodology/approachThis research proposes an optimal method for material handling in automobile assembly line. To solve the problem, several properties and definitions are proposed to solve the model more efficiently. Because of the non-deterministic polynomial-time-hard nature of the proposed problem, a Multi-objective Discrete Differential Evolution Algorithm with Variable Neighborhood Search (VNS-MDDE) is developed to solve the multi-objective problem.FindingsThe performances of VNS-MDDE are evaluated in simulation and the results indicate that the proposed algorithm is effective and efficient in solving BOGIHTS&FSDP problem.Originality/valueThis study is the first to take advantage of the robot's interactive functions for part supply in automobile assembly lines, which is both the challenge and trend of future intelligent logistics under the pressure of energy and resource. To solve the problem, a VNS-MDDE is developed to solve the multi-objective problem.

Optimal Network Design of Battery-Powered Electric Feeder Bus with Determination of Fleet Size and Number of Chargers

AbstractThis paper investigates an optimization problem regarding feeder bus network design for metro stations, based on the wide use of battery-powered electric buses. To characterize the problem,...

Electric vehicle fleet size for carsharing services considering on-demand charging strategy and battery degradation

This study addresses the tactical electric vehicle fleet size (EVFS) problem faced by carsharing service (CSS) providers while considering the operational vehicle assignment, vehicle relocation, and vehicle charging strategies (i.e., the charging duration at each station) in pursuit of profit maximization. To alleviate battery degradation and achieve cost-saving in the long term, we propose the on-demand charging strategy to determine fleet size. The novelty of this study lies in the incorporation of nonlinear battery wear cost incurred during the battery charging and discharging processes. A mixed-integer nonlinear programming (MINLP) model with concave and convex terms in the objective function is first developed for the EVFS problem. Piecewise linear approximation approach and outer-approximation method are employed to linearize the proposed model. Numerical experiments based on EVCARD, a one-way electric carsharing operator in China, are conducted to demonstrate the efficiency of the proposed model and solution method, as well as the necessity of incorporating the battery degradation into the fleet size determination of CSSs. The impacts of several key parameters, i.e., the daily fixed cost of EV and battery price, battery cycle efficiency, service charge, and relocation cost on the performance of one-way electric CSSs are also analyzed.

Fleet size determination for a mixed private and pooled on-demand system with elastic demand

The recent emergence of innovative mobility solutions is changing the mobility landscape in urban areas. However, it remains unknown how the combined operation of private and pooled on-demand services affect service performance and the required dimensioning of the fleet size for such services. This study develops a model to determine the fleet size of an on-demand system offering private service and pooled service, where the demand for these services is an outcome of modal choices. We investigate the fleet size required when taking either the perspective of Transit Planning Authority (Agency) or Service Provider (Operator). The model is implemented for the network of Amsterdam North. Results show that the objectives of Agency and Operator yield different total fleet sizes with the Agency requiring a larger fleet than the Operator and that the optimal scenario for the Agency would be the one where only private on-demand service is offered.

Joint design of multimodal transit networks and shared autonomous mobility fleets

Providing quality transit service to travelers in low-density areas, particularly travelers without personal vehicles, is a constant challenge for transit agencies. The advent of fully-autonomous vehicles (AVs) and their inclusion in mobility service fleets may allow transit agencies to offer better service and/or reduce their own capital and operational costs. This study focuses on the problem of allocating resources between transit patterns and operating (or subsidizing) shared-use AV mobility services (SAMSs) in a large metropolitan area. To address this question, a joint transit network redesign and SAMS fleet size determination problem (JTNR-SFSDP) is introduced, and a bi-level mathematical programming formulation and solution approach are presented. The upper-level problem modifies a transit network frequency setting problem (TNFSP) formulation via incorporating SAMS fleet size as a decision variable and allowing the removal of bus routes. The lower-level problem consists of a dynamic combined mode choice-traveler assignment problem (DCMC-TAP) formulation. The heuristic solution procedure involves solving the upper-level problem using a nonlinear programming solver and solving the lower-level problem using an iterative agent-based assignment-simulation approach. To illustrate the effectiveness of the modeling framework, this study uses traveler demand from Chicago along with the region’s existing multimodal transit network. The computational results indicate significant traveler benefits, in terms of improved average traveler wait times, associated with optimizing the joint design of multimodal transit networks and SAMS fleets compared with the initial transit network design.

Determining an Optimal Fleet Size for a Reliable Shared Automated Vehicle Ride-Sharing Service

Shared Automated Vehicles (SAVs) have the potential to revolutionize the urban transport landscape by reducing congestions, air pollution, and traffic accidents. However, the rejection rate for the travelers’ requests can jeopardize the potential adoption of SAVs as a new sustainable mode. We present MATSim simulations of SAVs service requests and rejections in the Tel-Aviv Metropolitan Area (TAMA) in Israel and demonstrate that fleets of 50-150K vehicles could well serve the entire intra-metropolitan travel demand, with an average occupancy of ~2 compared to 1.1 passengers per vehicle today. Minimal fleet size of 50K SAVs is sufficient for serving TAMA users’ activities but carries a high level of daily rejections 6%. An increase to 100K vehicles reduces the overall rejection rate to 1.66% with the rejection rate for trips between the TAMA core and outskirts remaining higher than 20%. A larger fleet size does not seem to improve the level of service significantly. The operational implications for optimal fleet size determination are further discussed.

Joint Design of Multimodal Transit Networks and Shared Autonomous Mobility Fleets

Abstract Providing quality transit service to travelers in low-density areas, particularly travelers without personal vehicles, is a constant challenge for transit agencies. The advent of fully-autonomous vehicles (AVs) and their inclusion in mobility service fleets may allow transit agencies to offer better service and/or reduce their own capital and operational costs. This study focuses on the problem of allocating resources between transit patterns and operating (or subsidizing) shared-use AV mobility services (SAMSs) in a large metropolitan area. To address this question, a joint transit network redesign and SAMS fleet size determination problem (JTNR-SFSDP) is introduced, and a bi-level mathematical programming formulation and solution approach are presented. The upper-level problem modifies a transit network frequency setting problem (TNFSP) formulation via incorporating SAMS fleet size as a decision variable and allowing the removal of bus routes. The lower-level problem consists of a dynamic combined mode choice-traveler assignment problem (DCMC-TAP) formulation. The heuristic solution procedure involves solving the upper-level problem using a nonlinear programming solver and solving the lower-level problem using an iterative agent-based assignment-simulation approach. To illustrate the effectiveness of the modeling framework, this study uses traveler demand from Chicago along with the region’s existing multimodal transit network. The computational results indicate significant traveler benefits, in terms of improved average traveler wait times, associated with optimizing the joint design of multimodal transit networks and SAMS fleets compared with the initial transit network design.

A stochastic hybrid simulation-optimization approach towards haul fleet sizing in surface mines

ABSTRACTHaul fleet size determination is a critical task in any surface mining operation where the material is handled using the truck-and-shovel system. Although the problem of finding the optimum haulage fleet size has been thoroughly studied, there are two important shortcomings: disregarding the effects of downstream processes on the operation and ignoring the fleet management system effects. This paper presents an integrated simulation-optimization framework to address the haul fleet size determination problem surface mines and target the two shortcomings listed above. In the developed framework, the mining operation, the processing plants, and the operational decision tools communicate with each other to find the best size of the haul fleet required to meet the production schedule. Results of the study show that the developed framework is capable of handling the operation with 13% less number of trucks than the required number of trucks suggested by deterministic calculations.

Simulation-based Concrete Truck-Mixers Fleet Size Determination for On-Site Batch Plant Operation

Resource management depends on the particulars of the operational setting within which the project resources are being deployed. This paper analyses the operations of an on-site batch plant and the concrete supply process with the aid of simulation-based modeling. The objective of the study is the determination of the concrete truck fleet size that fits best the project needs. The model building process is described and key production parameters are identified. Data are collected to define activity durations and alternative scenarios are being examined by the use of sensitivity analysis. Simulation outputs are validated against the actual records and the practical implications of the deployed truck fleet size is examined against utilization and productivity criteria. The research findings indicate that the model- generated information aids construction managers in making informed decisions regarding the resource management strategy that is going to be implemented on site.

Fleet size determination for a truckload distribution center

SUMMARYThis work presents an analysis of the fleet size determination problem for a truckload distribution center in which each customer requests multi‐truckload services. A transformation is made to define this problem as a cutting stock problem which can be resolved by finding the proper set of patterns beneficial for an NP‐hard (non‐deterministic polynomial‐time hard) problem. The genetic algorithm (GA) is combined with cutting stock techniques to solve the problem. Experiments are carried out testing two types of problems, with and without time‐window constraints. To verify the solution quality obtained with the proposed approach, the problem is also solved using only GA. It is shown that the proposed approach can significantly improve the GA solution by 14.68%. Copyright © 2012 John Wiley & Sons, Ltd.

Tactical locomotive fleet sizing for freight train operations

Determination of fleet size of locomotives and of a policy to deadhead them are tactical issues that influence the level of customer service in a rail network. This paper considers a railroad system in which a priori freight train schedule does not exist. A simulation-based approach is proposed for tactical locomotive fleet sizing. The study shows that the throughput increases with the number of locomotives upto a certain level; after that the congestion caused by the movements of large number of locomotives in the capacity-constrained rail network offsets the potential benefit of a large fleet.

Concurrent specification of unit load sizes and automated guided vehicle fleet size in manufacturing system

Even though many Subproblems related to the design of automated guided vehicle (AGV) systems interact with one another, current design approaches of AGV systems tend to focus on solving one Subproblem at a time. Piecemeal solution leads to suboptimal design. What is required is a concurrent engineering design approach that integrates two or more Subproblems into a design model which, when solved, yields the optimal design parameters for the entire system. Three areas that are amenable to integrated design for AGV systems are unit load size specification, vehicle size selection, and fleet size determination. Even though the size and number of unit loads to be moved per period constitute major factors in the determination of vehicle requirements and the specification of vehicle size for AGV based systems, there is very little research done in the specification of load sizes to optimize on total vehicle requirements. In his paper, a procedure is presented for the selection of the best unit load sizes for all part types manufactured in a shop that employs AGVs for handling. The problem is modeled as a mathematical program and solved by a hybrid algorithm that includes numerical search, computer simulation, and statistical analysis. The decision criterion is based on the minimization of expected total manufacturing cost.

Optimum fleet size determination by queuing and simulation

Queuing theory applications in the field of earth-moving operations are reviewed. Using queuing theory and simulation techniques, a model is developed that can predict the productivity of one pusher and a fleet of scrapers under a given set of operating conditions. A computer program is developed for this purpose that interfaces Gaarslev's Queuing Model Program and Caterpillar's Vehicle Simulation Program. The new system can consider the effect of variable inter-arrival times and bunching and road and machine conditions. The developed computer system allows the user to perform a sensitivity analysis by varying the number of scrapers, thus determining the optimum fleet size based on the lowest cost per cubic yard of production.