A column generation approach to solve the crew re-scheduling problem

When tracks are out of service for maintenance during a certainperiod, trains cannot be operated on those tracks. This leads to amodified timetable, and results in infeasible rolling stock andcrew schedules. Therefore, these schedules need to be repaired.The topic of this paper is the rescheduling of crew.In this paper, we define the Crew Re-Scheduling Problem (CRSP).Furthermore, we show that it can be formulated as a large-scaleset covering problem. The problem is solved with a columngeneration based algorithm. The performance of the algorithm istested on real-world instances of NS, the largest passengerrailway operator in the Netherlands. Finally, we discuss somebenefits of the proposed methodology for the company.column generation;transportation;railways;crew re-scheduling;large-scale optimization

Service scheduling in garden maintenance

Neoturf is a Portuguese company working in the area of project, building and garden’s maintenance. Neoturf would like to have a procedure for scheduling and routing efficiently the clients from garden maintenance services. The company has two teams available during the whole year and an additional team during summer to handle all the maintenance jobs. Each team consists of two or three employees with a vehicle fully equipped with the tools that allow to carry out every kind of maintenance service. In the beginning of each year, the number and frequency of maintenance interventions to conduct during the year, on each client, are accorded. Each client is assigned to the same team and, usually, time windows are established so that visits to the client should occur only within these periods. As the Neoturf costumers’ are geographically spread over a wide region, the total distance on visiting clients is a factor that has a heavy weight on the costs of the company. Neoturf is concerned with reducing these costs, while satisfying the agreements with the clients

Robustness measure for fuzzy maintenance activities schedule.

International audienceSkills management in industry is one of the most important factors in order to obtain good performance with production means. Especially in the field of maintenance services where the different practical knowledge or skills are their working tools. We address, in this paper, both the assignment and scheduling problems that can be found in a maintenance service. Each task that has to be performed is characterized by the level of skill required. The problem lies with making the decision of which time is the right time for the assignment and scheduling of the correct resource to do the task. For human resources, all skill levels are different, they are considered as unrelated parallel machines. Our aim is to assign new tasks to the adequate resources by giving to the maintenance expert a good and robust possibility

Web-based Process Planning for Machine Tool Maintenance and Services

Providing maintenance and services for high value complex products would extend manufacturers’ responsibilities and benefits to the products' whole usable life, and provide the opportunities to re-use or re-manufacture some failed parts. Sophisticated Computer Numerical Control (CNC) machine tools in modern manufacturing systems are special products in that they are also used to manufacture other products, and their operation performance directly affects the quality of the manufactured parts as well as the performance of the entire manufacturing system. To ensure CNC machine tools’ consistent performance, appropriate and efficient maintenance and services are essential and this is more challenging as technologies become more sophisticated and the environment is more dynamic. Previous research was mainly focused on maintenance strategy and maintenance scheduling. Very little effort was devoted to providing operational guidance for maintenance process execution, i.e., providing service suppliers with detailed information about resources needed for maintenance such as tooling, consumables, materials and spare parts, as well as service steps including disassembly and assembly of the serviced products. In this project, planning maintenance operation sequences, schedules and resource allocation are the three main tasks for generating final maintenance plans. This paper will present a Collaborative Maintenance Planning System (CoMPS) which will manage information and knowledge to support decision making in maintenance process planning

Towards a Technician Marketplace using Capacity-Based Pricing

Today, industrial maintenance is organized as an on-call business: Upon a customer’ s service request, the maintenance provider schedules a service technician to perform the demanded service at a suitable time. In this work, we address two drawbacks of this scheduling approach: First, the provider typically prioritizes service demand based on a subjective perception of urgency. Second, the pricing of technician services is inefficient, since services are priced on a time and material basis without accounting for additional service quality (e.g. shorter response time). We propose the implementation of a technician marketplace that allows customers to book technician capacity for fixed time slots. The price per time slot depends on the remaining capacity and therefore incentivizes customers to claim slots that match their objective task urgency. The approach is evaluated using a simulation study. Results show the capabilities of capacity-based pricing mechanisms to prioritize service demand according to customers’ opportunity costs