Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

A quadrant shrinking heuristic for solving the dynamic multi-objective disaster response personnel routing and scheduling problem

In the aftermath of natural disasters there is a need to provide disaster relief services. These services are offered by diverse disaster relief personnel teams that are specialized in the provision of the required services, e.g., teams that set up temporary shelters, teams that are providing medical services. These services are provided during a rolling horizon and the demand and supply characteristics of the disaster relief system evolve dynamically over time. In this paper we are presenting a dynamic variant of the multi-objective disaster relief personnel routing and scheduling (DDRPRS) problem, which considers efficiency, fairness and transportation risk objectives. We introduce a Quadrant Shrinking Method (QSM) based heuristic algorithm to approximate the Pareto Optimal Solutions of the DDRPRS problem under consideration. The proposed algorithm considers the performance of the solutions over the entire planning horizon and their robustness over time in terms of their efficiency, fairness and transportation risk. We apply the proposed heuristic for routing and scheduling personnel involved in evacuation and medical operations using data from the 2018 Lombok Earthquake in Indonesia. Our heuristic implementation covers both the dynamic and static variants of the disaster relief personnel routing and scheduling problem. Computational results show that the proposed heuristic can generate in a short time sufficiently large number of Pareto Optimal Solutions which cover the entire Pareto frontier as indicated by the diverging behaviours of the Pareto Optimal Solutions and the associated hypervolume metrics

A multi-objective rolling horizon personnel routing and scheduling approach for natural disasters

The magnitude of the workload associated with the provision of emergency response services in the aftermath of natural disasters, coupled with limited availability of personnel for providing these services, leads to demand–supply imbalances with detrimental effects on the provision of the required services. In this context, personnel routing and scheduling decisions aim to meet the demand as fast as possible while at the same time they ensure fair provision of services among the impacted areas. Due to their excessive working hours, and their travel over unreliable transportation networks, personnel are prone to burnout effects and are exposed to risks derived from the unreliable condition of the disaster impacted transportation networks. To address these issues, we propose a novel Disaster Response Personnel Routing and Scheduling (DRPRS) model with efficiency, fairness and risk objectives, subject to working and resting related constraints. The proposed model can be applied to routing and scheduling decisions for different types of emergency response services, and takes into account the precedence relations among them. We solve the resulting multi-objective model lexicographically over a rolling horizon sequentially on a daily basis until the demand for all types of services considered is satisfied. We report results from the application of the proposed model for routing and scheduling personnel involved in the provision of evacuation and medical services in the context of 2018 Lombok Earthquake, Indonesia

RESPOND-OR:Multi-objective rolling horizon personnel routing and scheduling approach for natural disasters

The magnitude of the workload associated with the provision of emergency response services in the aftermath of natural disasters, coupled with limited availability of personnel for providing these services, leads to demand–supply imbalances with detrimental effects on the provision of the required services. In this context, personnel routing and scheduling decisions aim to meet the demand as fast as possible while at the same time they ensure fair provision of services among the impacted areas. Due to their excessive working hours, and their travel over unreliable transportation networks, personnel are prone to burnout effects and are exposed to risks derived from the unreliable condition of the disaster impacted transportation networks. To address these issues, we propose a novel Disaster Response Personnel Routing and Scheduling (DRPRS) model with efficiency, fairness and risk objectives, subject to working and resting related constraints. The proposed model can be applied to routing and scheduling decisions for different types of emergency response services, and takes into account the precedence relations among them. We solve the resulting multi-objective model lexicographically over a rolling horizon sequentially on a daily basis until the demand for all types of services considered is satisfied. We report results from the application of the proposed model for routing and scheduling personnel involved in the provision of evacuation and medical services in the context of 2018 Lombok Earthquake, Indonesia