Maintenance of power generators is essential for reliable and efficient electricity production. Because under maintenance are typically inactive, optimal planning activities must consider the impact outages on system operation. However, in hydropower systems finding a minimum cost schedule challenging optimization problem due to uncertainty water inflows nonlinearity hydroelectricity Motivated ...

Operations Research practitioners often want to model complicated functions that are difficult encode in their underlying optimisation framework. A common approach is solve an approximate model, and then use a simulation evaluate the true objective value of one or more solutions. We propose new integrating into itself. The idea run at each incumbent solution master problem. results used guide t...

Decomposition models with integer variables usually decompose into a master problem that comprises all the integer variables and subproblems, which evaluate the remaining variables. Subproblems with integer variables introduce additional difficulties and require the use of nonlinear duality theory. In this paper we address the solution of a mixed integer hydrothermal coordination problem combin...

The Shift Design Problem is an important optimization problem which arises when scheduling personnel in industries that require continuous operation. Based on the forecast, required staffing levels for a set of time periods, a set of shift types that best covers the demand must be determined. A shift type is a consecutive sequence of time periods that adheres to legal and union rules and can be...

Walter Rei, Michel Gendreau Département d’informatique et de recherche opérationnelle and Centre de recherche sur les transports, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Canada, H3C 3J7, {[email protected], [email protected]} Jean-François Cordeau, Patrick Soriano HEC and Centre de recherche sur les transports, Montréal, 3000 chemin de la Côte-Sainte-C...

The Benders decomposition algorithm has been successfully applied to a wide range of difficult optimization problems.This paper presents a state-of-the-art survey of this algorithm, with an emphasis on its use in combinatorial optimization. We discuss the classical algorithm, the impact of the problem formulation on its convergence, and the relationship to other decomposition methods. We introd...

We study project scheduling at a large IT services delivery center in which there are unpredictable delays. We apply robust optimization to minimize tardiness while informing the customer of a reasonable worst-case completion time, based on empirically determined uncertainty sets. We introduce a new solution method based on logic-based Benders decomposition. We show that when the uncertainty se...

This dissertation analyzes three scheduling problems motivated by real life situations. In many manufacturing and service industries, scheduling is an important decision-making process. Unfortunately, scheduling problems are often computationally challenging to solve, and even modeling a scheduling problem can be difficult. Chapter 2 considers single-facility non-preemptive scheduling problems ...