This study addresses a stochastic structure for generation companies (GenCoʼs) that participate in hydro-thermal self-scheduling with a wind power plant on short-term scheduling for simultaneous reserve energy and energy market. In stochastic scheduling of HTSS with a wind power plant, in addition to various types of uncertainties such as energy price, spinning /non-spinning reserve prices, unc...

zinc is the first modelling language which supports solver and technique independence. this means that a high level conceptual model can be automatically mapped into an appropriate low level design model for a specific solver or technique. to date, zinc uses three different techniques to solve a model: constraint programming (cp), local search (ls), and mixed integer programming (mip). in this ...

in recent years, supplier evaluation and selection, an important element in supply chain management, has been gaining attention in both academic literature and industrial practice. the mixed integer multi-objective non-linear programming model (mimonlp) presented in this paper aimed to evaluate and select the appropriate set of suppliers considering quantitative and qualitative criteria and in ...

We introduce stochastic integer programs with dominance constraints induced by mixed-integer linear recourse. Closedness of the constraint set mapping with respect to perturbations of the underlying probability measure is derived. For discrete probability measures, large-scale, block-structured, mixed-integer linear programming equivalents to the dominance constrained stochastic programs are id...

We present methods to synthesize cooperative strategies for multi-vehicle control problems using mixed integer linear programming. Complex multi-vehicle control problems are expressed as mixed logical dynamical systems. Optimal strategies for these systems are then solved for using mixed integer linear programming. We motivate the methods on problems derived from an adversarial game between two...

For many years the mathematical programming community has realized the practical importance of developing algorithmic tools for tackling mixed integer optimization problems. Given our ability to solve linear optimization problems efficiently, one is inclined to think that a mixed integer program with both continuous and discrete variables is easier than a pure integer programming problem since ...

presented here is a generalization of the implicit enumeration algorithm that can be applied when the objec-tive function is being maximized and can be rewritten as the difference of two non-decreasing functions. also developed is a computational algorithm, named linear speedup, to use whatever explicit linear constraints are present to speedup the search for a solution. the method is easy to u...

In this paper recently developed mixed-integer programming (MIP) tools to the problem of optimal siting and sizing of distributed generators in a distribution network. Here three methodologies for solving the DGPP via mixed-integer linear programming (MILP) and mixed-integer nonlinear programming (MINLP) approaches are compared. The single MILP approach uses the well-known DC linear approximati...

We present a generalization of the average shadow price in 0-1-Mixed Integer Linear Programming problems and its relation with bottlenecks including the analysis relative to the coefficients matrix of resource constraints. A mathematical programming approach to find the strategy for investment in resources is presented. KeywordsMixed Integer programming, Average shadow price, Bottlenecks, Resou...

This paper introduces tabu search for the solution of general linear integer problems. Search is done on integer variables; if there are continuous variables, their corresponding value is determined through the solution of a linear program, which is also used to evaluate the integer solution. The complete tabu search procedure includes an intensification and diversification procedure, whose eff...