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...

We consider mixed-integer linear programming (MIP) models of production planning problems known as the small bucket lot-sizing and scheduling problems. We present an application of a class of valid inequalities to the case with lost demand (stock-out) costs. Presented results of numerical experiments made for the the Proportional Lot-sizing and Scheduling Problem (PLSP) confirm benefits of such...

The International Timetabling Competition 2019 (ITC 2019) posed a university timetabling problem involving assigning classes to times and rooms for an entire semester while students required classes. We propose new mixed integer programming (MIP) formulation of the problem. MIP takes advantage different graph structures in conflict graphs construct strong constraints. In addition, we introduce ...

Linear integer constraints are one of the most important constraints in combinatorial problems since they are commonly found in many practical applications. Typically, encoding linear constraints to SAT performs poorly in problems with these constraints in comparison to constraint programming (CP) or mixed integer programming (MIP) solvers. But some problems contain a mix of combinatoric constr...

This paper presents a robust approach to solve Hoist Scheduling Problems (HSPs) based on an integration of Constraint Logic Programming (CLP) and Mixed Integer Programming (MIP). By contrast with previous dedicated models and algorithms for solving classes of HSPs, we deene only one model and run diierent solvers. The robust approach is achieved by using a CLP formalism. We show that our models...

We propose a network flow formulation for protein threading and show its equivalence with the shortest path problem on a graph with a very particular structure. The underying Mixed Integer Programming (MIP) model proves to be very appropriate for the protein threading problem–huge real-life instances have been solved in a reasonable time by using only a Mixed Integer Optimizer instead of a spec...

Most industrial model predictive controllers (MPC) use the traditional two-layer structure developed in the early 1980’s, where the upper layer defines optimal steady-state targets for inputs and outputs, while the lower layer calculates the control moves that drive the system towards these steady-state targets. Typically both layers use continuous quadratic programming (QP) formulations to der...

Most industrial model predictive controllers (MPC) use the traditional two-layer structure developed in the early 1980’s, where the upper layer defines optimal steady-state targets for inputs and outputs, while the lower layer calculates the control moves that drive the system towards these steady-state targets. As a rule, both layers use continuous quadratic programming (QP) formulations to de...

This paper aims at linking the work presented in Dauzère-Pérès et al. (1998) and more recently Kasapidis (2021) on multiresource flexible job-shop scheduling problem with nonlinear routes or equivalently arbitrary precedence graphs. In particular, we present a mixed integer linear programming (MIP) model constraint (CP) to formulate problem. We also compare theorems introduced propose new theor...

This paper addresses a multi-objective optimization problem for marine monitoring using USV. The objectives are to cover the maximum area with lowest energy cost while avoiding collisions. is solved an exact and heuristic methods. First, Mixed Integer Programming formulation proposed model USV problem. It consists of combination Covering Salesman Problem (CSP) Travelling Profit (TSPP). Then, we...