Have you ever asked yourself how to increase your efficiency in a regular daily work? At the end of a busy working day, you may find yourself with many unaccomplished tasks even if you came into the office early and left late. Making a schedule for your daily work will help you manage your time more efficiently. Scheduling is the art of figuring out when to do what so that you can achieve your goals with the resources at hand.
Scheduling problem is one of the most important subjects in operations research (OR) due to its wide applicability and inherent difficulty. However, the concepts of scheduling are very clear and simple to understand also for those not familiar with OR. OR evolved during World War II in Great Britain to find the most efficient usage of limited military resources by the application of quantitative techniques. Nowadays, resource allocation decisions still lie at the heart of OR problems.
Scheduling is a decision-making process of allocating resources over time to perform a collection of tasks. As a model builder, you can model the resources and tasks in every organization in different forms. For instance, the resources may be machines in a workshop or crews at a maintenance site. The tasks may involve processing a job on a machine in production scheduling or replacing a component of a system in maintenance scheduling. Each task may have a certain due date. Companies must meet due dates that have been committed to customers, as failure to do so may result in significant losses. The decision to provide multiple tasks on common resources results in the need for setup activities. Setup activities represent costly disruptions prior to the execution of a task (e.g. obtaining tools and cleaning up). The setup process is not a value added factor, and hence, it is desirable to increase the resource utilization by reducing the setups. Scheduling activities in such a way that the available resources are used in an efficient manner is not an easy matter, and it becomes even more complex if we consider the concerns of different parties and include several realistic constraints.
I am an operational researcher ("OR"-er) at heart, interested in modeling of complex real-world systems by considering different criteria to optimize or making a decision through. My research focus is on production and maintenance scheduling problems. In a production scheduling problem, a manufacturing company may need to decide how to best schedule workforce and assign jobs to machines in order to minimize the completion time of jobs and delays. Production scheduling plays a fundamental role in the manufacturing of goods for all kinds of real world scenarios including the electronics, paper and textile industries. In a maintenance scheduling problem, an infrastructure manager may need to decide how to find the best sequence of maintenance actions (e.g. repair and replacement) for each component of the system in order to minimize the maintenance costs. Effective maintenance scheduling plays also an important role in many industries, especially in areas where the loss resulting from a system failure is significant. For the system used in the delivery of services, such as railways, roadways, electricity distribution networks, and distributed pipelines, it is extremely important to avoid failure during actual operation because it can be dangerous or disastrous. By using resources efficiently in production and maintenance scheduling problems, we can help companies to operate according to budget and time constraints.
Mathematical modeling is the main building block of OR, and turning a scheduling problem into the solution arise from its modeling. A mathematical model is an abstract version of real-world problem that uses mathematical language to describe the behavior of system. The real-world problem has usually so many facets that modelers cannot take everything into account, so the most important aspects should be kept into the model. A good model is simple, extensible, reusable, traceable, and truthful with a clearly specified purpose. The concept of scheduling has been studied by many researchers for various systems; however, each system has its own objective and constraints and it can be modeled in thousand ways based on modeler's point of view. Building good models is an art. Essentially, good models are not those in papers but models that are in use.
Last updated: 31.8.2017