The Nurse Rostering Problem in COVID-19 emergency scenario

Healthcare facilities are struggling in fighting the spread of COVID-19. While machines needed for patients such as ventilators can be built or bought, healthcare personnel is a very scarce resource that cannot be increased by hospitals in a short period. Furthermore, healthcare personnel is getting sick while taking care of infected people, increasing this shortage … Read more

Mixed-Integer Linear Programming for Scheduling Unconventional Oil Field Development

The scheduling of drilling and hydraulic fracturing of wells in an unconventional oil field plays an important role in the profitability of the field. A key challenge arising in this problem is the requirement that neither drilling nor oil production can be done at wells within a specified neighborhood of a well being fractured. We … Read more

Distributionally Robust Optimization under Decision-Dependent Ambiguity Set with an Application to Machine Scheduling

We introduce a new class of distributionally robust optimization problems under decision dependent ambiguity sets. In particular, as our ambiguity sets, we consider balls centered on a decision-dependent probability distribution. The balls are based on a class of earth mover’s distances that includes both the total variation distance and the Wasserstein metrics. We discuss the … Read more

A Polynomial-time Algorithm with Tight Error Bounds for Single-period Unit Commitment Problem

This paper proposes a Lagrangian dual based polynomial-time approximation algorithm for solving the single-period unit commitment problem, which can be formulated as a mixed integer quadratic programming problem and proven to be NP-hard. Tight theoretical bounds for the absolute errors and relative errors of the approximate solutions generated by the proposed algorithm are provided. Computational … Read more

Flexible Job Shop Scheduling Problems with Arbitrary Precedence Graphs

A common assumption in the shop scheduling literature is that the processing order of the operations of each job is sequential; however, in practice there can be multiple connections and finish-to-start dependencies among the operations of each job. This paper studies flexible job shop scheduling problems with arbitrary precedence graphs. Rigorous mixed integer and constraint … Read more

Scheduling Post-disaster Repairs in Electricity Distribution Networks with Uncertain Repair Times

Natural disasters, such as hurricanes, large wind and ice storms, typically require the repair of a large number of components in electricity distribution networks. Since power cannot be restored before the completion of repairs, optimally scheduling the available crews to minimize the cumulative duration of the customer interruptions reduces the harm done to the affected … Read more

Logic-based Benders Decomposition and Binary Decision Diagram Based Approaches for Stochastic Distributed Operating Room Scheduling

The distributed operating room (OR) scheduling problem aims to find an assignment of surgeries to ORs across collaborating hospitals that share their waiting lists and ORs. We propose a stochastic extension of this problem where surgery durations are considered to be uncertain. In order to obtain solutions for the challenging stochastic model, we use sample … Read more

Dynamic Design Of Reserve Crew Duties For Long Haul Airline Crew

Airlines need crew to operate their flights. In case of crew unavailability, for example due to illness, the airline often uses reserve crew to still be able to operate the flight. In this paper, we apply a simulation-based optimization method to determine how much and on which days reserve crew needs to be scheduled. This … Read more

Migration from Sequence to Schedule in Total Earliness and Tardiness Scheduling Problem

Services must be delivered with high punctuality to be competitive. The classical scheduling theory offers to minimize the total earliness and tardiness of jobs to deliver punctual services. In this study, we developed a fully polynomial-time optimal algorithm to transform a given sequence, the permutation of jobs, into its corresponding minimum cost schedule, the timing … Read more

Data-Driven Distributionally Robust Appointment Scheduling over Wasserstein Balls

We study a single-server appointment scheduling problem with a fixed sequence of appointments, for which we must determine the arrival time for each appointment. We specifically examine two stochastic models. In the first model, we assume that all appointees show up at the scheduled arrival times yet their service durations are random. In the second … Read more