Rolling horizon scheduling algorithm for dynamic vehicle scheduling system

Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and then the problem is simplified asthe asymmetrical travelingsalesman problem with time windows. The rolling horizon scheduling algorithm (RHSA) to solve thisdynamic problem is proposed. By the rolling of time horizon, the RHSA can adapt to the problem'sdynamic change and reduce the computation time by dealing with only part of the customers in eachrolling time horizon. Then, its three factors, the current customer window, the scheduling of thecurrent customer window and the rolling strategy, are analyzed. The test results demonstrate theeffectiveness of the RHSA to solve the dynamic vehicle scheduling problem.

MULTITASK SCHEDULING IN NETWORKED CONTROL SYSTEMS WITH APPLICATION TO LARGE SCALE VEHICLE CONTROL

Aiming at scheduling problems of networked control system （NCS） used to fulfill motion synthesis and cooperation control of the distributed multi-mechatronic systems, the differences of network scheduling and task scheduling are compared, and the mathematic description of task scheduling is presented. A performance index function of task scheduling of NCS according to task balance and traffic load matching principles is defined. According to this index, a static scheduling method is designed and implemented to controlling task set simulation of the DCY100 transportation vehicle. The simulation results are applied successfully to practical engineering in this case so as to validate the effectiveness of the proposed performance index and scheduling algorithm.

Optimization for vehicle scheduling in iron and steel works based on semi-trailer swap transport

In order to solve internal logistics problems of iron and steel works,such as low transportation efficiency of vehicles and high transportation cost,the production process and traditional transportation style of iron and steel works were introduced.The internal transport tasks of iron and steel works were grouped based on cluster analysis according to demand time of the transportation.An improved vehicle scheduling model of semi-trailer swap transport among loading nodes and unloading nodes in one task group was set up.The algorithm was designed to solve the vehicle routing problem with simultaneous pick-up and delivery(VRPSPD) problem based on semi-trailer swap transport.A solving program was written by MATLAB software and the method to figure out the optimal path of each grouping was obtained.The dropping and pulling transportation plan of the tractor was designed.And an example of semi-trailer swap transport in iron and steel works was given.The results indicate that semi-trailer swap transport can decrease the numbers of vehicles and drivers by 54.5% and 88.6% respectively compared with decentralized scheduling in iron and steel works,and the total distance traveled reduces by 43.5%.The semi-trailer swap transport can help the iron and steel works develop the production in intension.

Improved Ant Colony Algorithm for Vehicle Scheduling Problem in Airport Ground Service Support

Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for current operational demands is proposed to study optimization algorithms for vehicle scheduling.The model is based on the constraint relationship of the initial operation time,time window,and gate position distribution,which gives an improvement to the ant colony algorithm(ACO).The impacts of the improved ACO as used for support vehicle optimization are compared and analyzed.The results show that the scheduling scheme of refueling trucks based on the improved ACO can reduce flight delays caused by refueling operations by 56.87%,indicating the improved ACO can improve support vehicle scheduling.Besides,the improved ACO can jump out of local optima,which can balance the working time of refueling trucks.This research optimizes the scheduling scheme of support vehicles under the existing conditions of airports,which has practical significance to fully utilize ground service resources,improve the efficiency of airport ground operations,and effectively reduce flight delays caused by ground service support.

The Information Modeling and Intelligent Optimization Method for Logistics Vehicle Routing and Scheduling with Multi-objective and Multi-constraint

The vehicle routing and scheduling (VRS) problem with multi-objective and multi-constraint is analyzed, considering the complexity of the modern logistics in city economy and daily life based on the system engineering. The objective and constraint includes loading, the dispatch and arrival time, transportation conditions,total cost,etc. An information model and a mathematical model are built,and a method based on knowledge and biologic immunity is put forward for optimizing and evaluating the programs dimensions in vehicle routing and scheduling with multi-objective and multi-constraints. The proposed model and method are illustrated in a case study concerning a transport network, and the result shows that more optimization solutions can be easily obtained and the method is efficient and feasible. Comparing with the standard GA and the standard GA without time constraint,the computational time of the algorithm is less in this paper. And the probability of gaining optimal solution is bigger and the result is better under the condition of multi-constraint.

Optimized vehicle scheduling and filling model based on effective space and integrated solving algorithm

We established an integrated and optimized model of vehicle scheduling problem and vehicle filling problem for solving an extremely complex delivery mode-multi-type vehicles, non-full loads, pickup and delivery in logistics and delivery system. The integrated and optimized model is based on our previous research result-effective space method. An integrated algorithm suitable for the integrated and optimized model was proposed and corresponding computer programs were designed to solve practical problems. The results indicates the programs can work out optimized delivery routes and concrete loading projects. The model and algorithm have many virtues and are valuable in practice.

Economical Aspects of the Vehicle Scheduling Optimization

The paper deals with the vehicle scheduling problem related to regional public transport. Linear programming methods are used to solve the problem. A mathematical model is created including the constraints and the objective function minimizing costs and the number of vehicles. A minimum costs and a number of vehicles are forced at the same time by special economical input data analysis and an allocation of costs. Determining of the costs coefficients is done by three methods, which differs primarily by how much of the total costs they take into account. The decomposition of the set of lines into disjoint subsets can be used instead of the ＂direct＂ optimization. The decomposition has proven to be a suitable alternative in solving large optimization problems. The problem was applied to optimize vehicle scheduling in the region, which is situated in the north-east of the Czech Republic. There is used Xpress-IVE software, which solve the problem by simplex algorithm and branch and bound method. Research results show that there are large reserves in the organization of public transport. The implementation of the new vehicle scheduling would bring significant costs reductions in amount of at least 10% for the optimal solution and in amount of about 10% for the decomposition solution. The number of drivers could be decreased and the total time of the vehicles being outside the garage could be also reduced by at least 10%.

A Heuristic Method for Vehicle Scheduling Problems

This paper presents a sequential optimum algorithm for vehicle schedulingproblem, which includes obtaining initial theoretical solution, adjustingsolution, forming initial routes and adjustins routes. This method can beapplied to general transportation problems with multiple depots and multiplevehicle types on complex network. In comparison with manual scheduling ofChengdu Transportation Company II, the result shows that this method isreasonable, feasible and applicable.

AGV Scheduling Optimization of Automated Port Based on Disruption Management

The recent rapid development of China’s foreign trade has led to the significant increase in waterway transportation and automated container ports. Automated terminals can significantly improve the loading and unloading efficiency of container terminals. These terminals can also increase the port’s transportation volume while ensuring the quality of cargo loading and unloading, which has become an inevitable trend in the future development of ports. However, the continuous growth of the port’s transportation volume has increased the horizontal transportation pressure on the automated terminal, and the problems of route conflicts and road locks faced by automated guided vehicles (AGV) have become increasingly prominent. Accordingly, this work takes Xiamen Yuanhai automated container terminal as an example. This work focuses on analyzing the interference problem of path conflict in its horizontal transportation AGV scheduling. Results show that path conflict, the most prominent interference factor, will cause AGV scheduling to be unable to execute the original plan. Consequently, the disruption management was used to establish a disturbance recovery model, and the Dijkstra algorithm for combining with time windows is adopted to plan a conflict-free path. Based on the comparison with the rescheduling method, the research obtains that the deviation of the transportation path and the deviation degree of the transportation path under the disruption management method are much lower than those of the rescheduling method. The transportation path deviation degree of the disruption management method is only 5.56%. Meanwhile, the deviation degree of the transportation path under the rescheduling method is 44.44%.

Intelligent fire information system based on 3D GIS

Background This work aims to build a comprehensive and effective fire emergency management system based on the Internet of Things(IoT)and achieve an actual intelligent fire rescue.A smart fire protection information system was designed based on the IoT.A detailed analysis was conducted on the problem of rescue vehicle scheduling and the evacuation of trapped persons in the process of fire rescue.Methods The intelligent fire visualization platform based on the three-dimensional(3D)Geographic Information Science(GIS)covers project overview,equipment status,equipment classification,equipment alarm information,alarm classification,alarm statistics,equipment account information,and other modules.The live video accessed through the visual interface can clearly identify the stage of the fire,which facilitates the arrangement of rescue equipment and personnel.The vehicle scheduling model in the system primarily used two objective functions to solve the Pareto Non-Dominated Solution Set Optimization:emergency rescue time and the number of vehicles.In addition,an evacuation path optimization method based on the Improved Ant Colony(IAC)algorithm was designed to realize the dynamic optimization of building fire evacuation paths.Results The experimental results indicate that all the values of detection signals were significantly larger in the smoldering fire scene at t=17s than the initial value.In addition,the probability of smoldering fire and the probability of open fire were relatively large according to the probability function of the corresponding fire situation,demonstrating that this model could detect fire.Conclusions The IAC algorithm reported here avoided the passages near the fire and spreading areas as much as possible and took the safety of the trapped persons as the premise when planning the evacuation route.Therefore,the IoT-based fire information system has important value for ensuring fire safety and carrying out emergency rescue and is worthy of popularization and application.

Vehicle and charging scheduling of electric bus fleets:A comprehensive review

Transit electrification has emerged as an unstoppable force,driven by the considerable environmental benefits it offers.However,the adoption of battery electric buses is still impeded by their limited flexibility,a constraint that necessitates adjustments to current bus scheduling plans.Consequently,this study aspires to offer a thorough review of articles focused on battery electric bus scheduling.Moreover,we provide a comprehensive review of 42 papers on electric bus scheduling and related studies,with a focus on the most recent developments and trends in this research domain.Despite this extensive review,our findings reveal a paucity of research that takes into account the robustness of electric bus scheduling.Furthermore,we highlight the critical areas of considering diverse charging modes in electric bus scheduling and integrated planning of electric buses,which have not been adequately explored but hold the potential to greatly boost the effectiveness of electric bus systems.Through this synthesis,we hope that readers could acquire a thorough comprehension of the studies in this field and be motivated to address the identified research gaps,thus propelling the progress of transit electrification.

A Discrete Artificial Bee Colony Algorithm for Stochastic Vehicle Scheduling

Vehicle scheduling plays a profound role in public transportation.Especially,stochastic vehicle scheduling may lead to more robust schedules.To solve the stochastic vehicle scheduling problem(SVSP),a discrete artificial bee colony algorithm(DABC)is proposed.Due to the discreteness of SVSP,in DABC,a new encoding and decoding scheme with small dimensions is designed,whilst an initialization rule and three neighborhood search schemes(i.e.,discrete scheme,heuristic scheme,and learnable scheme)are devised individually.A series of experiments demonstrate that the proposed DABC with any neighborhood search scheme is able to produce better schedules than the benchmark results and DABC with the heuristic scheme performs the best among the three proposed search schemes.

Analysis on the gear-shifting schedule of hydraulic automatic transmission

With an advanced foreign hydraulic automatic transmission as the objective,an analytical method for the gear-shifting schedule is proposed.First the demanded maximum gradient of test is estimated.Then a test scheme and analytical procedure is formulated by initial test and hypothetical shift parameters.Finally through gear-shifting tests under different road conditions,load,accelerator pedal position limitation,throttle opening and output shaft speed are found to be the gear-shifting parameters.Under a common road condition,the gear-shifting schedule is a double-parameter schedule.Based on the driver＇s demands on braking and dynamic performance,different shift schedules are made under downhill,uphill and quick releasing acceleration pedal conditions.The operation criteria of down-shift schedule on abrupt grade are proposed.

A Decision Support Method for Truck Scheduling and Storage Allocation Problem at Container

Truck scheduling and storage allocation, as two separate subproblems in port operations, have been deeply studied in past decades. However, from the operational point of view, they are highly interdependent. Storage allocation for import containers has to balance the travel time and queuing time of each container in yard. This paper proposed an integer programming model handling these two problems as a whole. The objective of this model is to reduce congestion and waiting time of container trucks in the terminal so as to decrease the makespan of discharging containers. Due to the inherent complexity of the prob-lem, a genetic algorithm and a greedy heuristic algorithm are designed to attain near optimal solutions. It shows that the heuristic algorithm can achieve the optimal solution for small-scale problems. The solutions of small-and large-scale problems obtained from the heuristic algorithm are better than those from the genetic algorithm.

Grid Integration of Electric Vehicles for Economic Benefits:A Review

Emissions from the internal combustion engine(ICE) vehicles are one of the primary cause of air pollution and climate change. In recent years, electric vehicles(EVs) are becoming a more sensible alternative to these ICE vehicles. With the recent breakthroughs in battery technology and large-scale production, EVs are becoming cheaper. In the near future,mass deployment of EVs will put severe stress on the existing electrical power system(EPS). Optimal scheduling of EVs can reduce the stress on the existing network while accommodating large-scale integration of EVs. The integration of these EVs can provide several economic benefits to different players in the energy market. In this paper, recent works related to the integration of EV with EPS are classified based on their relevance to different players in the electricity market. This classification refers to four players: generation company(GENCO), distribution system operator(DSO), EV aggregator, and end user. Further classification is done based on scheduling or charging strategies used for the grid integration of EVs. This paper provides a comprehensive review of technical challenges in the grid integration of EVs along with their solution based on optimal scheduling and controlled charging strategies.

A bi-level optimization framework for charging station design problem considering heterogeneous charging modes

Purpose–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.Design/methodology/approach–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.Findings–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.Originality/value–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.