Resource-constrained scheduling with non-constant capacity and non-regular activities

This work is inspired by very challenging issues arising in space logistics. The problem of scheduling a number of activities, in a given time elapse, optimizing the resource exploitation is discussed. The available resources are not constant, as well as the request, relative to each job. The mathematical aspects are illustrated, providing a time-indexed MILP … Read more

On the NP-Completeness of the Multi-Period Minimum Spanning Tree Problem

In this note, we consider the Multi-period Minimum Spanning Tree Problem (MMST), a variant of the well known Minimum Spanning Tree Problem (MST), that consists in the fol- lowing. Given a connected and undirected graph G and a finite discrete time horizon, one has to schedule the moment in time edges are added to a … Read more

A Two-Stage Stochastic Program for Multi-shift, Multi-analyst, Workforce Optimization with Multiple On Call Options

Motivated by a cybersecurity workforce optimization problem, this paper investigates optimizing staffing and shift scheduling decisions given unknown demand and multiple on call staffing options at a 24/7 firm with three shifts per day, three analyst types, and several staffing and scheduling constraints. We model this problem as a two-stage stochastic program and solve it … Read more

Steiner tree network scheduling with opportunity cost of time

This paper points out the impact of opportunity cost of time (high discount rate or high rate of time preference, time-dependent profits, etc.) in designing real-world Steiner trees like electricity, gas, water, or telecommunications networks. We present the Steiner Tree Scheduling Problem which consists of finding a Steiner tree in an activity-on-arc graph that spans … Read more

Adaptive Elective Surgery Planning Under Duration and Length-Of-Stay Uncertainty: A Robust Optimization Approach

Scheduling elective surgeries is a complicated task due to the coupled effect of multiple sources of uncertainty and the impact of the proposed schedule on the downstream units. In this paper, we propose an adaptive robust optimization model to address the existing uncertainty in surgery duration and length-of-stay in the surgical intensive care unit. The … Read more

A Study of Three-Period Ramp-Up Polytope

We study the polyhedron of the unit commitment problem, and consider a relaxation involving the ramping constraints. We study the three-period ramp-up polytope, and describe the convex-hull using a new class of inequalities. Citation[1] J. Ostrowski, M. F. Anjos, and A. Vannelli, \Tight mixed integer linear programming formulations for the unit commitment problem,” Power Systems, … Read more

Improving Public Transport Accessibility via Provision of a Dial-a-Ride Shuttle-Bus Service, Incorporating Passenger Travel-Mode Heterogeneity

In many real-world transportation systems, passengers are often required to make a number of interchanges between different modes of transport. As cities continue to grow, a greater number of these connections tend to occur within centrally located Transport Hubs. In order to encourage the uptake of public transport in major cities, it is important for … Read more

Integer Programming Approaches for Appointment Scheduling with Random No-shows and Service Durations

We consider a single-server scheduling problem given a fixed sequence of appointment arrivals with random no-shows and service durations. The probability distribution of the uncertain parameters is assumed to be ambiguous and only the support and first moments are known. We formulate a class of distributionally robust (DR) optimization models that incorporate the worst-case expectation/conditional … Read more

The Value of Stochastic Programming in Day-Ahead and Intraday Generation Unit Commitment

The recent expansion of renewable energy supplies has prompted the development of a variety of efficient stochastic optimization models and solution techniques for hydro-thermal scheduling. However, little has been published about the added value of stochastic models over deterministic ones. In the context of day-ahead and intraday unit commitment under wind uncertainty, we compare two-stage … Read more

An MILP-MINLP decomposition method for the global optimization of a source based model of the multiperiod blending problem

The multiperiod blending problem involves binary variables and bilinear terms, yielding a nonconvex MINLP. In this work we present two major contributions for the global solution of the problem. The rst one is an alternative formulation of the problem. This formulation makes use of redundant constraints that improve the MILP relaxation of the MINLP. The … Read more