Total Number Of Trucks Research Articles

An optimization model for collaborative logistics among carriers in vehicle routing problems with cross-docking

PurposeCollaborative Logistics (CL) and merging operations are crucial strategies for reducing costs and improving service in transportation companies. This study proposes a model for optimizing efficiency in supply chain networks through inbound and outbound Collaborative Logistics implementation among the carriers in centralized, coordinated networks with cross-docking.Design/methodology/approachA mixed-integer non-linear programming model is developed to determine the optimal truck-goods assignment while gaining economies of scale through mixing multiple less-than-truckload (LTL) products with different weight-to-volume ratios. Unlike the previous studies that have considered Collaborative Logistics from the cost and profit-sharing perspective, the proposed model seeks to determine an appropriate form of Collaborative Logistics in the VRP.FindingsThis article shows that in a three-echelon supply chain consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. This approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of collaborative logistics among the carriers was discussed. In a three-echelon SC consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. Using a combination of experimental analysis and optimization process, it was recommended that managers be cautious that too much (full or complete) or no collaboration can result in SC performance deterioration.Originality/valueThe suggested approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of Collaborative Logistics among the carriers was discussed.

Optimizing the Hub-and-Spoke Network with Drone-Based Traveling Salesman Problem

The hub-and-spoke network (HSN) design generally assumes direct transportation between a spoke node and its assigned hub, while the spoke’s demand may be far less than a truckload. Therefore, the total number of trucks on the network increases unnecessarily. We form a drone-based traveling salesman problem (TSP-D) for the cluster of spokes assigned to a hub. A truck starts from the hub, visiting each spoke node of the hub in turn and finally returning to the hub. We propose a three-stage decomposition model to solve the HSN with TSPD (HSNTSP-D). The corresponding three-stage decomposition algorithm is developed, including cooperation among variable neighborhood search (VNA) heuristics and nearest neighbor algorithm (NNA), and then the spoke-to-hub assignment algorithm through the reassignment strategy (RA) method. The performance of the three-stage decomposition algorithm is tested and compared on standard datasets (CAB, AP, and TR). The numerical analysis of the scenarios shows that whether it is trunk hub-level transportation or drone spoke-level transportation, it integrates resources to form a scale effect, which can reduce transport devices significantly, as well as decreasing the investment and operating costs.

Techno-econo-environmental comparisons of zero- and low-emission heavy-duty trucks

This paper presents the results of techno-econo-environmental modelling of options to decarbonise fleets of four-axle trucks in the quarrying sector. The key parameter used to evaluate the performance of transitioning from diesel heavy-duty trucks (HDT) to zero- or low-emission heavy-duty trucks (ZLETs) is the total cost of carbon abatement (TCA). TCA is calculated by using the total cost of truck ownership on a discounted cost per km basis (TCO) and well-to-wheel (WTW) life-cycle greenhouse gas (GHG) emissions. TCO includes the costs of the vehicle, infrastructure, fuel, maintenance, and resale, and is evaluated for five different powertrain configurations: (1) battery electric heavy-duty truck (BET), (2) plug-in hybrid electric heavy-duty truck (PHET), (3) diesel internal combustion engine heavy-duty truck (ICET), (4) diesel-hydrogen dual-fuel engine heavy-duty truck (DFET), and (5) hydrogen fuel cell electric heavy-duty truck (FCET). Combinations of wind and/or grid electricity supply BETs and PHETs. Hydrogen is also produced from the same energy sources via electrolysis for DFETs and FCETs. The hourly electricity and hydrogen production and refuelling performance for each powertrain are assessed for on- and off-grid systems. The production capacity and costs can be optimally sized using the total number of trucks, annual operational distance, and fuel economy to meet the annual fuel demand for each powertrain. Results show the fuel cost is the largest contributor to TCOs for all powertrains except the BET, which is dominated by infrastructure cost. The TCOs for all powertrains in off-grid system are higher compared to on-grid systems, which require smaller equipment sizes. In contrast, more WTW emissions for all powertrains can be abated by off-grid system compared to on-grid system. The minimum TCAs for fleets of 100 trucks in on- and off-grid systems are found for BETs and DFETs, respectively. The total number of trucks has a significant impact on the reduction of TCO and TCA. Higher carbon tax (€/ tonne of CO₂ emitted) in the future can also help the ZLETs to be more competitive.

Bin packing with lexicographic objectives for loading weight- and volume-constrained trucks in a direct-shipping system

We consider a packing problem that arises in a direct-shipping system in the food and beverage industry: Trucks are the containers, and products to be distributed are the items. The packing is constrained by two independent quantities, weight (e.g., measured in kg) and volume (number of pallets). Additionally, the products are grouped into the three categories: standard, cooled, and frozen (the latter two require refrigerated trucks). Products of different categories can be transported in one truck using separated zones, but the cost of a truck depends on the transported product categories. Moreover, splitting orders of a product should be avoided so that (un-)loading is simplified. As a result, we seek for a feasible packing optimizing the following objective functions in a strictly lexicographic sense: minimize the (1) total number of trucks; (2) number of refrigerated trucks; (3) number of refrigerated trucks which contain frozen products; (4) number of refrigerated trucks which also transport standard products; (5) and minimize splitting. This is a real-world application of a bin-packing problem with cardinality constraints a.k.a. the two-dimensional vector packing problem with additional constraints. We provide a heuristic and an exact solution approach. The heuristic meta-scheme considers the multi-compartment and item fragmentation features of the problem and applies various problem-specific heuristics. The exact solution algorithm covering all five stages is based on branch-and-price using stabilization techniques exploiting dual-optimal inequalities. Computational results on real-world and difficult self-generated instances prove the applicability of our approach.

Deep Learning with Bidirectional Long Short-Term Memory for traffic flow Prediction

With the development of cities, the total number of trucks has increased year by year. Traffic flow forecasting has become an indispensable part of the cargo transportation industry and directly affects the development of the transportation industry. In the field of traffic flow prediction, Long Short-Term Memory(LSTM) model has advantages in processing time series, but it cannot extract the periodicity in time series. Therefore, in this experiment, a Bidirectional Long Short-Term Memory (BLSTM) model was constructed to predict traffic flow in the road network. It is worth mentioning that this article considers the non-parametric model autoregressive integrated moving average model (ARIMA) and the parametric model recurrent neural network (RNN) to compare and analyze with LSTM. Data from Guangwu Toll Station, Zhengzhou city, China were used to calibrate and evaluate the models. The experimental results show that the performance of RNN based on deep learning such as BLSTM and LSTM model is better than that of ARIMA. In order to better illustrate the advantages of BLSTM model, we comprehensively considered the performance effects of four models under morning peak, evening peak and flat peak. Experiments have proved that BLSTM has good nonlinear fitting ability and anti-noise ability, and the average prediction accuracy reaches 92.873%.

Metaheuristic algorithm for solving the multi-objective vehicle routing problem with time window and drones

In some special rescue scenarios, the needed goods should be transported by drones because of the landform. Therefore, in this study, we investigate a multi-objective vehicle routing problem with time window and drone transportation constraints. The vehicles are used to transport the goods and drones to customer locations, while the drones are used to transport goods vertically and timely to the customer. Three types of objectives are considered simultaneously, including minimization of the total energy consumption of the trucks, total energy consumption of the drones, and the total number of trucks. An improved artificial bee colony algorithm is designed to solve the problem. In the proposed algorithm, each solution is represented by a two-dimensional vector, and the initialization method based on the Push-Forward Insertion Heuristic is embedded. To enhance the exploitation abilities, an improved employed heuristic is developed to perform detailed local search. Meanwhile, a novel scout bee strategy is presented to improve the global search abilities of the proposed algorithm. Several instances extended from the Solomon instances are used to test the performance of the proposed improved artificial bee colony algorithm. Experimental comparisons with the other efficient algorithms in the literature verify the competitive performance of the proposed algorithm.

The analysis of overloaded trucks in indonesia based on weigh in motion data (east of sumatera national road case study)

Overloaded trucks phenomena generally common in developing countries where the traffic control is poor. In Indonesia, the percentage of overloaded trucks can reach more than 60% in the total number of trucks and may be one of the substantial factors that reduce the service life of the road pavements. This paper presents the analysis results of the weigh in motion survey data at East of Sumatera National Road (Jalintim) in Indonesia and the impact of overloaded trucks on the pavement. For the analysis the simplified approach was used, the axle loads were converted into representative single-axle loads based on 4th power formula by AASHTO 1993 equation. The vehicle damage factor of vehicles is presented and will be compared with the Highways National Standard to estimate the remaining service life of pavement and IRI value prediction. The analysis showed that the vehicle damage factor that determined from weigh in motion data is extremely greater than vehicle damage factor of the national standard in Indonesia which may lead to accelerated deterioration, reducing the service life of the pavement structures and significantly influence the IRI value.

Modeling of peak hour factor on highways and arterials

The peak hour factor characterizes the fluctuations of traffic flow based on the busiest 15 minutes during the peak hour. This parameter is used in the process of evaluating the traffic flow conditions such as capacity and Level of Service. The paper examines the impact of traffic on the PHF, and results in calibrated models that estimate the PHF of different road categories based on a large data set obtained from a recent cordon and screen line traffic survey of Tel Aviv metropolitan area in Israel. The PHF was estimated for four road categories based on the independent variables: total number of vehicles per lane per direction, total number of trucks per direction, and total number of buses per direction. The PHF resulted in the following ranges, based on the superior calibrated models with or without the impact of the heavy vehicle variables: 0.88–0.99 for rural freeways and multilane highways, 0.81–0.97 for two-lane rural highways, 0.922–0.972 for urban and suburban freeways and multilane highways, and 0.91–0.98 for urban arterials. These volume based ranges partially include the uniform values proposed by the Highway Capacity Manual (2000, 2010). The rural model calibrations could be beneficial in estimating traffic flow rates for traffic engineering analysis when traffic counting is incomplete or not achievable. The urban models need further examination.

In This Issue

In This Issue

A study of economic efficiency in port security inspection

SUMMARYThe purpose of this paper is to study an economic efficiency for the prediction of additional truck turnaround time and for determining the number of the port security inspection equipment required at a terminal inspection station. The economic efficiency with six base models was developed to assist terminal operators' decision‐making. In addition, this study developed an optimal procedure that terminal operators could use to optimally run in terms of various statistics processes including exponential, deterministic, and others, seeking a solution that was beneficial for both terminal operators and truckers.As a result of this research of the additional cargo turnaround time for port security delay, the following conclusion can be drawn and made. The average additional delay time in the inspection station is very dependent on the inspection rate of the lower stage. The higher weighted inspection time based on raising security level allows less number of trucks to be inspected, which will derive high delay in the inspection station. Increase of rate of Green Lane usage will allow a decrease in the arrival rate, which may derive improvement of inspection equipment efficiency and average delay time at the inspection station. In multiple stage model, total number of trucks and delay time very closely follow those of low inspection stage rate and number of inspection units. Free Lane is to be followed by Customs‐Trade Partnership Against Terrorism and standardization of customs, packing, loading and unloading, documents, procedure, and exchange working in each country. Copyright © 2012 John Wiley & Sons, Ltd.

AN ALGORITHM FOR THE GENERALIZED VEHICLE ROUTING PROBLEM WITH BACKHAULING

The Vehicle Routing Problem with Backhauling deals with the supply of finished goods from a depot to a number of delivery points, and picking up returnable items and bringing them back to the depot using a fleet of trucks. Traditionally, the objective of the problem has been to determine the truck routes such that the total number of trucks and/or the total distance traveled/total route cost are minimized. Most of the papers available in the literature in this connection deal with problems where the linehaul (having a demand for finished goods) and backhaul (having items to be returned to the depot) customers are different, and a customer may be visited by at most one truck limiting demand and returns at a location by the capacity of the truck. In this paper, we allow the linehaul and backhaul customers to be the same leading to simultaneous delivery and pickup at a customer location, and also there is no restriction on the quantity demanded at (to be returned from) a customer location. As such a customer may be visited by more than one truck and more than once by the same truck. We developed a Mixed Integer Linear programming (MILP) formulation of the problem and a route construction heuristic. The heuristic averaged 80 ms for 110 problems tested, and in 78 of them the heuristic costs were either equal to the optimal costs or at most equal to the upper bounds on the optimal costs obtained after running the optimization package for 30 min. Optimal solutions were obtained for 28 problems at an average time of 295 ms. The heuristic could match the optimal solutions for 22 of these problems at an average time of 71 ms.

Snow Emergency Vehicle Routing with Route Continuity Constraints

New results are presented from continuing research dealing with development of a decision support system to assist the Maryland State Highway Administration Office of Maintenance staff in designing snow emergency routes for Calvert County, Maryland. By taking into account some of the more realistic constraints, an attempt is made to solve two problems. One involves minimizing the total number of trucks, and the second one involves minimizing the total deadhead distance given the number of trucks. The two problems do not result in identical solutions in general. The first problem is formulated as the well-known capacitated minimum spanning tree (CMST) problem. The second problem is also formulated as a CMST problem but with an approximate function for total deadhead distance. Some application results are also reported, which indicate that using such a system can achieve improvements in service and savings in operational costs.

Effect of Truck Loads on Bridges

This paper determines the truck‐load spectra for highway bridges. The weigh‐in‐motion data was collected at weigh stations located on Highways I‐75 and I‐94. The total number of trucks considered in this study is over 600,000. For each truck, the measured parameters include axle loads and axle spacings. Bridge load is considered in terms of moments and shears. Therefore, maximum moments and shears are calculated for each truck for various span lengths. The results are plotted on the normal‐probability paper to facilitate statistical interpretations. The cumulative distribution functions of moments and shears are used to extrapolate the results to predict the maximum forces in longer time periods, up to 75 years. Truck counts were carried out on U.S.‐23 and I‐94 to determine the number of trucks per lane and multiple presence frequency in lane and side by side.