This study addresses the scheduling problem where every job requires several types of
resources. At every point in time, the capacity of resources is limited. When necessary, the …

This paper proposes a joint decomposition method that combines Lagrangian
decomposition and generalized Benders decomposition, to efficiently solve multiscenario …

The main purpose of solving a classical generation capacity expansion problem is to ensure
that, in the medium-to long-term time frame, the electric utility has enough capacity available …

Prefabrication and modularization are a growing trend in the construction industry.
Efficiencies of the operation of construction prefabrication and modularization (CP&M) …

The two-stage stochastic program with probabilistic constraints is studied by assuming
normally distributed uncertain parameters. At stage I, the decision, represented by discrete …

Stochastic integer programming (SIP) combines the difficulty of uncertainty and non-
convexity, and constitutes a class of extremely challenging problems to solve. Efficiently …

This paper studies a two-stage stochastic facility location and network flow problem with
uncertainty in demand, supply, network availability, transportation costs, and cost of facility …

Large-scale mixed-integer linear programming (MILP) problems, such as those from two-
stage stochastic programming, usually have a decomposable structure that can be exploited …

This paper proposes a model for reliable facility location with distribution protection. The
proposed model utilizes site-dependent failure probabilities and random link disruptions. It …

Рассмотрены алгоритмы для решения це-лочисленных квазиблочных задач
оптимизации. Проана-лизированы современные методы декомпозиции. Иссле-дован …