We consider optimization problems related to the scheduling of multi-echelon assembly supply chain (MEASC) networks that have applications in the recovery from large-scale disruptive events. Each manufacturer within this network assembles a component from a series of sub-components received from other manufacturers. We develop scheduling decision rules that are applied locally at each manufacturer and … Read more
We consider the clique problem with multiple-choice constraints (CPMC) and characterize a case where it is possible to give an efficient description of the convex hull of its feasible solutions. This new special case, which we call staircase compatibility, generalizes common properties in several applications and allows for a linear description of the integer feasible … Read more
The clique problem with multiple-choice constraints (CPMC) represents a very common substructure in many real-world applications, for example scheduling problems with precedence constraints. It consists in finding a clique in a graph whose nodes are partitioned into subsets, such that exactly one node from each subset is chosen. Even though we can show that (CPMC) … Read more
In this work, we study the problem of scheduling courses and instructors in the Mathematics Department at the United States Naval Academy (USNA) in a resilient manner. Every semester, the department needs to schedule around 70 instructors and 150-180 course sections into 30 class periods and 30 rooms. We formulate a stochastic integer linear program … Read more
Demand for healthcare services is growing rapidly in Australia and across the world, and rising healthcare expenditure is increasing pressure on sustainability of government-funded healthcare systems. In Australia, elective surgery waiting lists are growing and hospitals are struggling with a capacity shortage. To keep up with the rising demand, we need to be more efficient … Read more
We consider a semi-online version of the problem of scheduling a sequence of jobs of different lengths on two uniform machines with given speeds $1$ and $s$. Jobs are revealed one by one (the assignment of a job has to be done before the next job is revealed), and the objective is to minimize the … Read more
This paper presents a new model for online decision making. Motivated by the health care delivery application of dynamically allocating patients to procedure rooms in outpatient procedure centers, the online stochastic extensible bin packing problem is described. The objective is to minimize the combined costs of opening procedure rooms and utilizing overtime to complete a … Read more
We address a class of deterministic scheduling problems in which two agents compete for the usage of a single machine. The agents have their own objective functions and submit in each round an arbitrary, unprocessed task from their buffer for possible selection. In each round the smaller of the two submitted tasks is chosen and … Read more
We study an incremental network design problem, where in each time period of the planning horizon an arc can be added to the network and a maximum flow problem is solved, and where the objective is to maximize the cumulative flow over the entire planning horizon. After presenting two mixed integer programming (MIP) formulations for … Read more
We study server scheduling in multiclass service systems under stochastic uncertainty in the customer arrival volumes. Common practice in such systems is to first identify staffing levels, and then determine schedules for the servers that cover these targets. We propose a new stochastic integer programming model that integrates these two decisions, which can yield lower … Read more