Routing Scheduling Research Articles

The Migratory Beekeeping Routing Problem: Model and an Exact Algorithm

Apiculture has gained worldwide interest because of its contributions to economic incomes and environmental conservation. In view of these, migratory beekeeping, as a high-yielding technique, is extensively adopted. However, because of the lack of an overall routing plan, beekeepers who follow the experiential migratory routes frequently encounter unexpected detours and suffer losses when faced with problems such as those related to nectar source capacities and the production of bee products. The migratory beekeeping routing problem (MBRP) is proposed based on the practical background of the commercial apiculture industry to optimize the global revenue for beekeepers by comprehensively considering nectar source allocation, migration, production and sales of bee products, and corresponding time decisions. The MBRP is a new variant of the vehicle routing problem but with significantly different production time decisions at the vertices (i.e., nectar sources). That is, only the overlaps between residence durations and flowering periods generate production benefits. Different sales visits cause different gains from the same products; in turn, these lead to different production time decisions at previously visited nectar source locations and even change the visits for production. To overcome the difficulty resulting from the complicated time decisions, we utilize the Dantzig–Wolfe decomposition method and propose a revised labeling algorithm for the pricing subproblems. The tests, performed on instances and a real-world case, demonstrate that the column generation method with the revised labeling algorithm is efficient for solving the MBRP. Compared with traditional routes, a more efficient overall routing schedule for migratory beekeepers is proposed. Summary of Contribution. Based on the practical background of commercial apiculture industry, this paper proposes a new type of routing problem named the migratory beekeeping routing problem (MBRP), which incorporates the selection of productive nodes and sales nodes as well as the production time decision at the productive nodes on a migratory beekeeping network. To overcome the difficulty resulting from the complicated time decisions, we utilize the Dantzig–Wolfe decomposition method and propose a revised labeling algorithm for the pricing subproblems. The tests, performed on instances and a real-world case, demonstrate that the column generation method with the revised labeling algorithm is efficient for solving the MBRP. Compared with traditional routes, a more efficient overall routing schedule for migratory beekeepers is proposed. Therefore, this paper is congruent with, and contributes to, the scope and mission of INFORMS Journal on Computing, especially the area of Network Optimization: Algorithms & Applications.

Route assignment and scheduling with trajectory coordination

We study the problem of finding optimal routes and schedules for multiple vehicles traveling in a network. Vehicles may have different origins and destinations, and must coordinate their trajectories to keep a minimum distance from each other at any time. We determine a route and a schedule for each vehicle, which possibly requires vehicles to wait at some nodes. Vehicles are heterogeneous in terms of their speed on each arc, which we assume is known and constant once in motion. Applications of this problem include air and maritime routing, where vehicles maintain a steady cruising speed as well as a safety distance to avoid collision. Additional related problems arise in the transportation of hazardous materials and in military operations, where vehicles cannot be too close to each other given the risk posed to the population or the mission in case of a malicious attack. We discuss the hardness of this problem and present an exact formulation for its solution. We devise an exact solution algorithm based on a network decomposition that exploits the sparsity of the optimal solution. We illustrate the performance of our methods on real and randomly generated networks.

Speeding Up On-Line Route Scheduling for an Autonomous Robot Through Pre-Built Paths

SUMMARYToday, robots can be found helping humans with their daily tasks. Some tasks require the robot to visit a set of locations in the environment efficiently, like in the Traveling Salesman Problem. As indoor environments are maze-like areas, feasible paths connecting locations must be computed beforehand, so they can be combined during the scheduling, which can be impracticable for real-time applications. This work presents an on-line Route Scheduling supported by a Fast Path Planning Method able to adjust pre-built paths. Experiments were carried out with virtual and real robots to evaluate time and quality of tours.

Design of Flexible Vehicle Scheduling Systems for Sustainable Paratransit Services

The aging population has led to an increase in the variety and volume of transportation demands by people facing travel difficulties. Hence, transportation organisations need to provide flexible and sustainable paratransit services to meet these increasing demands. In this study, we investigate the design of flexible vehicle scheduling systems in order for a community organisation to serve more people and achieve higher operational efficiency. We analyse and propose a system design based on user requirements for different types of paratransit types. Further, we identify an integrated service option and process flow for dial-a-ride passengers to ride on a vehicle with schedule route passengers. Because this option involves a complex decision, we formulate the problem as a two-stage decision model. To verify the effectiveness of our proposed design, we perform numerical simulations and conduct a case study by collaborating with a transportation organisation. We found that the proposed system would enable the organisation to serve more people with fewer vehicles but without an increase in the travelling time. These results demonstrate the importance of a flexible vehicle scheduling system for accessible transportation organisations to sustain their service operations.

Modeling of the collections process in the blood supply chain: A literature review

Human blood is a scarce resource and its role in healthcare is fundamental, with donated blood saving the lives of many on a daily basis. The blood supply chain is responsible for the transfer of blood from donor to the recipient, but the availability of such an invaluable resource as human blood is ultimately attributable to the many voluntary donors. Thus, the efficiency of the collection of donated blood is crucial to the downstream effectiveness of the blood supply chain. We provide a detailed review on the use of quantitative methods for the process of blood collection from donors. We describe the functional areas which are appointment scheduling, collection policy, crisis situation, donor demographics, location/clinic planning, staff utilization and vehicle routing. Furthermore, we analyze the existing literature with regards to methods, modeling objectives and the planning levels such as strategic, tactical and operational. Finally, we break down the articles into whether or not case studies lead to the implementation of the methods in practice. In total, we review 46 relevant publications on the intersection between OR/MS and other disciplines. We use our presented framework to categorize the existing approaches and highlight gaps such as scheduling of both staff and appointments for blood donation clinics.

The Online Distribution System of Inventory-Routing Problem with Simultaneous Deliveries and Returns Concerning CO2 Emission Cost

This study attempts to consider CO2 emission cost to propose an online distribution system of inventory-routing problem with simultaneous deliveries and returns (IRPSDRCO2). The proposed IRPSDRCO2 mathematical models will be developed to find the total inventory routing cost, the CO2 emission cost, the optimal delivery routes, the economic order quantities, the optimal reordering points, the optimal service levels, the optimal common review interval, and the optimal maximum inventory levels for all retail stores delivered in these scheduled routes. The proposed IRPSDRCO2 model further applies the savings method, the target insert heuristic method, the target exchange heuristic method, and the repeated target heuristic method to find the optimal solution and the related scheduled routing plan. The sensitivity analyses will be conducted for this proposed IRPSDRCO2 model based on different parameters to provide very helpful decision-making information for a distribution system design. The performance of the proposed repeated target heuristic method is demonstrated to be better than most of four other combination methods regarding both the inventory routing cost and CPU running time. Consequently, it should be very helpful for logistics firms to design their distribution system by following the structure and the detailed procedure flow of the online distribution system developed by this study.

Medical waste collection considering transportation and storage risk

We consider a Periodic Load-dependent Capacitated Vehicle Routing Problem (PLCVRP) encountered by healthcare centers and medical waste collection companies for the design of a weekly inventory routing schedule to transport medical wastes to treatment sites. In addition to minimization of transportation risk, occupational risk related to temporary storage of hazardous wastes at the healthcare centers is considered. The transport risk on each arc is dependent on the weight of hazardous medical waste on the vehicle when it traverses that arc. We devise a decomposition based heuristic algorithm to solve this problem. We analyze the characteristics of the PLCVRP’s solutions with respect to four different criteria: (i) transport and occupational risk, (ii) transport risk, (iii) occupational risk, and (iv) transportation cost. Solving different versions of PLCVRP reveals that minimizing both transport and occupational risk on the network can aid decision makers to develop a better routing schedule in terms of the imposed risk of hazardous medical waste. Experimental results confirm the efficiency of our heuristic. We present a case study to illustrate solution attributes obtained by our solution methodology. The case study is based on medical waste management in Dolj, Romania.

Development of a New Ship Adaptive Weather Routing Model Based on Seakeeping Analysis and Optimization

This paper provides a new adaptive weather routing model, based on the Dijkstra shortest path algorithm, aiming to select the optimal route that maximizes the ship performances in a seaway. The model is based on a set of ship motion-limiting criteria and on the weather forecast maps, providing the sea state conditions the ship is expected to encounter along the scheduled route. The new adaptive weather routing model is applied to optimize the scheduled route in the Northern Atlantic Ocean of the S175 containership, assumed as a reference vessel, based on the weather forecast data provided by the Global WAve Model (GWAM). In the analysis, both wave and combined wind/swell wave conditions are embodied to investigate the incidence on the optimum route assessment. Furthermore, the effect of the vessel speed on the optimum route detection is also investigated. Current results clearly show that it is possible to achieve appreciable improvements, up to 50% of the ship seakeeping performances, without excessively increasing the route length and the voyage duration.

Priority Based Routing and Link Scheduling for Cognitive Radio Networks

Priority Based Routing and Link Scheduling for Cognitive Radio Networks

Integrated Emergency Response for Distribution Network Maintenance and Recovery After Natural Disasters

This paper proposes a two-stage method of outage management for distribution network maintenance and recovery after natural disasters. In the first stage, all the fault points are clustered based on their distances from the depots and the availability of repair resources. The second stage solves the repair and restoration problems based on clustering results. With the aim of maximizing the picked-up loads in the shortest time, the routing schedule of the fleet is finally obtained. A mixed-integer linear programming model is developed to solve the co-optimization problem, considering the distribution network operation constraints and the constraints of routing repair crews, which are scheduled based on the resource availability, traveling time and maintenance time. The proposed method is verified on the modified IEEE 34-bus distribution system with multiple damages.

Digital technologies and new mobility

New types of mobility for people started to appear with the development of digitalization in various fields of transport industry. The article discusses the development trends of digital technologies in transport sector. The current situation of the use of digital technologies in transport is observed. Forecasts of the development and introduction of new technologies in digitalization are given. The author presents the overview and forecasts of the need for regulation of transport, taking into account modern technologies as well as the overview of new types of mobility for remote cities where it is not possible to create scheduled routes. The analysis and review of such directions of transport as sharing are presented. The advantages and disadvantages brought by car sharing in cities are substantiated. The analysis of the policies of different cities in stimulating people to transition to general economy and sharing cars is presented. As a result the overview of the advantages and disadvantages of carpooling system is reflected. Necessary legal regulation of carpooling and control over this type of activity are proposed. The article touches upon the issue of the fight against mass motorization through the use of vehicle sharing.

Elastic Virtualized Network Security Based on Multi-Tenant using Progressive Route Scheduling in a Cloud Data Center

Information security in the cloud has become a serious problem on the Internet. There are safety standards created by the resource in traditional computing. The public cloud providers, secure transfer, and the use of public resources due to the availability of the Internet is the cloud facing distributed data centers. Providing the required level of security, approaching adopting various security components such as security watchdog, IDS / IPS system, security framework, access control framework, security management and so on. In this proposed system to improve the data transmission security to introduce proposed algorithm Elastic virtualized network security (eVNS) for extended security service which utilizes the progressive route scheduling (PRS) and promotes the security consumption for Inbound rule based on the virtualized security load balancer. We have presented a virtual cloud for a network that is secure and robust security group protocols by any compromised or faulty node in the network. In contrast to the traditional snapshot aggregation approach in data centers, the eVNS-PRS proposed algorithm resembles the unicasting it's sensed information to create a new target security group based on the routing table. This makes the system more fault-tolerant and increases the availability of information in the network. Simulations performed with the proposed algorithm have demonstrated its effectiveness.

A Gibbs sampling based coordination scheduling method with fixed I/O constraint

Distributed production technology is the basic technology of modern production. Distributed production needs to consider the fixed input and output constraint, which is different from traditional centralized production. The objective of distributed production scheduling with fixed I/O constraint is to find the optimal scheduling route in production network. In this paper, we proposed the GSS (Gibbs Sampling Scheduling) method to schedule the schedulable jobs, according to a scheduling metric. GSS guarantees each device has opportunities to be allocated, to reduce the load on critical devices. The scheduling metric utilizes PCM (processing cost model) and TCM (transportation cost model) as parameters. The PCM represents the impact of schedulable jobs on the unscheduled jobs. The TCM represents the importance of devices’ positions in the production network. We designed experiments to analyze the parameters of the GSS, and carried out the test on makespan and load balance. These experiments can verify the effectiveness and efficiency of the proposed GSS method.

CAR: heuristics for the inventory routing problem

Vendor managed inventory (VMI) is a streamlined approach to inventory and order fulfillment and is a system in which vendors continuously and automatically replenish a trading partner’s inventory. Vendors must ensure appropriate quantities of storages at the point of demand and must ensure optimal distribution plans, including routing of the distribution vehicles. This problem is known as the inventory routing problem (IRP) and seeks to integrate the routing of vehicles used for collection and distribution, with conventional inventory management. This paper addresses an IRP with a manufacturer that supplies a product using a fleet of vehicles to a set of warehouses over a defined time horizon. We develop a mixed integer linear program to determine the optimal allocation and the routing schedule for warehouses over the defined time horizon. To solve this problem, we propose a three-phase heuristic approach, called CAR: clustering of receiver nodes, allocation of quantities to these nodes, and routing of delivery vehicles through clusters of nodes. Computational studies are carried out and experimental trials conducted over a large number of data sets provide encouraging results and show usefulness of the solution approaches. The proposed ILP would provide optimal solution to the problem but it demands huge computational effort. However, CAR2, a proposed heuristic, is able to get solutions 7.41% better than the upper bound solutions obtained from CPLEX. These approaches can easily be implemented into existing VMI systems.

Design of an Integrated Remote and Ground Sensing Monitor System for Assessing Farmland Quality.

Quality monitoring is important for farmland protection. Here, high-resolution remote sensing data obtained by unmanned aerial vehicles (UAVs) and long-term ground sensing data, obtained by wireless sensor networks (WSNs), are uniquely suited for assessing spatial and temporal changes in farmland quality. However, existing UAV-WSN systems are unable to fully integrate the data obtained from these two monitoring systems. This work addresses this problem by designing an improved UAV-WSN monitoring system that can collect both high-resolution UAV images and long-term WSN data during a single-flight mission. This is facilitated by a newly proposed data transmission optimization routing protocol (DTORP) that selects the communication node within a cluster of the WSN to maximize the quantity of data that can be efficiently transmitted, additionally combining individual scheduling algorithms and routing algorithms appropriate for three different distance scales to reduce the energy consumption incurred during data transmission between the nodes in a cluster. The performance of the proposed system is evaluated based on Monte Carlo simulations by comparisons with that obtained by a conventional system using the low-energy adaptive clustering hierarchy (LEACH) protocol. The results demonstrate that the proposed system provides a greater total volume of transmitted data, greater energy utilization efficiency, and a larger maximum revisit period than the conventional system. This implies that the proposed UAV-WSN monitoring system offers better overall performance and enhanced potential for conducting long-term farmland quality data collection over large areas in comparison to existing systems.

Train punctuality analysis in a rolling stock perspective

This paper studies how time delays spread through the railway system. We evaluate timetable and rolling stock interaction in relation to medium size delays. In particular, we study the connection between arrival and departure delays for trains that are operated by the same rolling stock individual. We studied one year of data for trains circulating in the Oslo area.Research questions in this study are:What is the connection between arrival and departure delays for the same piece of rolling stock?How can delays be tracked through the route schedules and the rolling stock circulation plan?Punctuality analysis was performed to investigate if there is a connection between arrival and departure delays. A correlation analysis of the arrival delays and the corresponding departures was done in order to find the possible connection.There was a connection between the size of arrival delays and the size of the corresponding departure delays. We found a threshold at around 20 minutes. An arrival delay over this threshold is expected to cause departure delays. Below the threshold most of the arrival delays are absorbed.

Simulation of intercepting bus stations in a major city

The article discusses the experience of developing and testing a methodology for studying the movement of buses on scheduled routes in intercity and suburban traffic from the bus terminal of a major city. The AnyLogic 8 University simulation package was used for visual representation of traffic, which allows us to get quantitative characteristics of traffic on an hourly schedule as a result. Based on the results of the study, a logistics approach was developed to determine the location of transport hubs "bus terminal/bus station", as a system of intercepting bus stations that should be integrated into the route network of the major city.

Обеспечение гарантии доставки информации в бор товой сети космического аппар ата на основе интерфейса SpaceWire

Nowadays SpaceWire is regarded as a perspective aerospace data transmission interface standard. This paper gives an analysis of a guaranteed information delivery of SpaceWire networks. The result of the analysis showed key problems that did not allow using this standard in real-time networks. A method was developed and proposed to guarantee the information delivery in the SpaceWire network based on scheduled routing. Tests using a software model of the modified network were performed. The results obtained confirmed the efficiency of the method used to ensure the guarantee of information delivery in the network. It is shown that a network with a modified protocol stack meets real-time requirements.

Joint Online Coflow Optimization Across Geo-Distributed Datacenters

Growing data volumes have been generated, stored and processed across geographically distributed datacenters. Processing such geo-distributed datasets should consider task or job placement, heterogeneous available link bandwidth, and routing decisions. Thus optimizing the transmissions of inter-datacenter flows, especially coflows that capture application-level semantics, is important. However, prior solutions on coflow scheduling either merely ignore routing or fix the endpoint placement. This article focuses on the problem of jointly considering endpoint placement, coflow scheduling, and coflow routing to minimize the average coflow completion time (CCT) across geo-distributed datacenters. This paper first presents the system model and problem formulation, then derives a randomized approximation algorithm for a single coflow. After that it also proposes an online algorithm to handle the complex cases of multiple coflows. Through theoretical analysis, a proof that the proposed algorithms have a non-trivial competitive ratio is given. Results from extensive simulations demonstrate that the proposed algorithms can significantly reduce the CCT of coflows and at the same time, have similar algorithm run time, compared with the state-of-the-art solutions.

United Health Services: Transportation Optimization

This project is based off the desire to improve the efficiency and customer service of the United Health Services transportation departments to minimize fuel costs, turnaround time, mileage, and duplicate deliveries by May 2019. United Health Services, a medical care provider in southern New York State, has two delivery and transportation departments that service 60 facilities. Materials Handling has two drivers and a weekly schedule and oversees the delivery of various medical supplies such as bandages, syringes, and crutches. External Transportation is staffed by 12 drivers and delivers time sensitive, patient-oriented supplies such as clean and used linen, specimens, and mail, utilizing a daily schedule. The goal of the project is to merge the two departments, focusing on route schedules and the loading and unloading processes, to improve the information flow and product flow of both operations.