Many optimal decision problems in scientific, engineering, and public sector applications
involve both discrete decisions and nonlinear system dynamics that affect the quality of the …

Electric vehicles (EVs) have been proposed as a key technology to help cut down the
massive greenhouse gas emissions from the transportation sector. Unfortunately, because …

Chance-constrained programming (CCP) is one of the most difficult classes of optimization
problems that has attracted the attention of researchers since the 1950s. In this survey, we …

We derive new mixed-integer quadratic, quadratically constrained, and second-order cone
programming models of distribution system reconfiguration, which are to date the first …

This paper surveys results on the NP-hard mixed-integer quadratically constrained
programming problem. The focus is strong convex relaxations and valid inequalities, which …

This paper provides a survey of recent progress and software for solving convex Mixed
Integer Nonlinear Programs (MINLP) s, where the objective and constraints are defined by …

We study mixed integer nonlinear programs (MINLP) s that are driven by a collection of
indicator variables where each indicator variable controls a subset of the decision variables …

We study several joint facility location and inventory management problems with stochastic
retailer demand. In particular, we consider cases with uncapacitated facilities, capacitated …

We propose a robust optimization approach to address a multiperiod inventory control
problem under ambiguous demands, that is, only limited information of the demand …

This paper focuses on the optimal operation of water supply networks. We model water
supply networks using hydraulic constraints and formulate a joint optimal pump scheduling …