This paper addresses a class of two-stage robust optimization models with an exponential
number of scenarios given implicitly. We apply Dantzig–Wolfe decomposition to exploit the …

We develop a constraint generation solution method for robust optimization problems in
radiation therapy in which the problems include a large number of robust constraints. Each …

We investigate a facility location problem with modular capacity under demand uncertainty
arising at Hydro-Québec, the largest public utility in Canada. We propose a mathematical …

The goal of radiation therapy (RT) is to eliminate cancerous cells by directing radiation
beams to the hit the cancer target while sparing the surrounding healthy tissue. In breast …

There are many applications of planning, scheduling, and routing problems in healthcare
systems. Efficiently solving these problems can help healthcare managers provide higher …

This paper addresses a class of two-stage robust optimization models with an exponential
number of scenarios given implicitly. We apply Dantzig–Wolfe decomposition to exploit the …

This dissertation presents mathematical models and algorithms that draw from optimization
and statistics and are motivated by practical problems in operations management. We …

We develop a constraint generation solution method for robust optimization problems in
radiation therapy in which the problems include a large number of robust constraints. Each …