As part of the day-ahead market clearing process, MISO solves one of the most challenging Security Constrained Unit Commitment (SCUC) models. This paper introduces several developments on MIP SCUC formulation that result in significant performance improvement. Numerical results based on MISO data are presented. Index Terms – Electricity market, mixed integer programming, security constrained un...

The paper presents two new compilation schemes of Decomposable Negation Normal Form (DNNF) theories into Conjunctive Normal Form (CNF) and Linear Integer Programming (MIP), respectively. We prove that the encodings have useful properties such as unit propagation on the CNF formula achieves domain consistency on the DNNF theory. The approach is evaluated empirically on random as well as real-wor...

Decomposition has proved to be one of the more effective tools for the solution of large-scale problems, especially those arising in stochastic programming. A decomposition method with wide applicability is Benders’ decomposition, and has been applied to both stochastic programming, as well as integer programming problems. However, this method of decomposition relies on convexity of the value f...

An optimization problem arising in the design of optical fibre networks is discussed. A network contains client nodes, each installed on one or more SONET rings. A constraint programming model of the problem is described and compared with a mixed integer programming formulation. In the CP model the search is decomposed into two stages; first partially solving the problem by deciding how many ri...

Multi-cluster environments are composed of multiple clusters of computers that act collaboratively, thus allowing computational problems that require more resources than those available in a single cluster to be treated. However, the degree of complexity of the scheduling process is greatly increased by the heterogeneity of resources and the co-allocation process, which distributes the tasks of...

The purpose of the paper is to present a hybrid algorithm to solve a transportation optimization model with random demand parameters and network design variables. At first, the classical deterministic linear transportation model with network design 0-1 variables is introduced. Then, randomness is considered for demand parameters and modeled by here-and-now approach. The obtained scenario-based ...

Given a bi-directed graph modeling telecommunication network, and set of origin-destination pairs representing traffic requests (commodities) along with their associated Service Function Chains (SFCs), the Virtual Network Placement Routing Problem (VNFPRP) aims to find, for each commodity, one latency-constrained routing path that visits required Functions in specific order. The function instal...

This paper provides an efficient computational approach to solve the mixed integer programming (MIP) model developed by Tarim and Kingsman (2004) for calculating the parameters of an (R,S) policy in a finite horizon with nonstationary stochastic demand and service level constraints. Given the replenishment periods, we characterize the optimal order-up-to levels for the MIP model and use it to g...

due to the considerable growth in the worldwide container transportation, optimization of container terminal operations is becoming highly needed to rationalize the use of logistics resources. for this reason, we focus our study on the quay crane scheduling problem (qcsp), which is a core task of managing maritime container terminals. from this planning problem arise two decisions to be made: t...