Synthesis of optimal double-rail logic networks using NOR-OR gates by integer programming.

"Supported in part by ... Grant no. NSF GJ-503."

Computational experience in all-integer, binary variable, integer programming problems using Gomory's all-integer algorithm,

Bibliographical footnotes.

Implicit enumeration algorithm of integer programming on Illiac IV,

Bibliography: p. 29.

Optimum network design using NOR-OR gates by integer programming.

"Supported in part by ... Grant no. NSF GJ-503."

Heuristic algorithm for computing reversal distance with multigene families via binary integer programming

Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE

An Interactive Method of Linear Mixed Integer Multicriteria Optimization

The paper describes a learning-oriented interactive method for solving linear mixed integer problems of multicriteria optimization. The method increases the possibilities of the decision maker (DM) to describe his/her local preferences and at the same time it overcomes some computational difficulties, especially in problems of large dimension. The method is realized in an experimental decision support system for finding the solution of linear mixed integer multicriteria optimization problems.

Nonparametric tests of collectively rational consumption behavior: an integer programming procedure

We present an IP-based nonparametric (revealed preference) testing procedure for rational consumption behavior in terms of general collective models, which include consumption externalities and public consumption. An empirical application to data drawn from the Russia Longitudinal Monitoring Survey (RLMS) demonstrates the practical usefulness of the procedure. Finally, we present extensions of the testing procedure to evaluate the goodness-of-…t of the collective model subject to testing, and to quantify and improve the power of the corresponding collective rationality tests.

Allocating reforestation areas for sediment flow minimization: an integer programming formulation and a heuristic solution method

Policy and decision makers dealing with environmental conservation and land use planning often require identifying potential sites for contributing to minimize sediment flow reaching riverbeds. This is the case of reforestation initiatives, which can have sediment flow minimization among their objectives. This paper proposes an Integer Programming (IP) formulation and a Heuristic solution method for selecting a predefined number of locations to be reforested in order to minimize sediment load at a given outlet in a watershed. Although the core structure of both methods can be applied for different sorts of flow, the formulations are targeted to minimization of sediment delivery. The proposed approaches make use of a Single Flow Direction (SFD) raster map covering the watershed in order to construct a tree structure so that the outlet cell corresponds to the root node in the tree. The results obtained with both approaches are in agreement with expert assessments of erosion levels, slopes and distances to the riverbeds, which in turn allows concluding that this approach is suitable for minimizing sediment flow. Since the results obtained with the IP formulation are the same as the ones obtained with the Heuristic approach, an optimality proof is included in the present work. Taking into consideration that the heuristic requires much less computation time, this solution method is more suitable to be applied in large sized problems.

Coordinated Scheduling of Wind-Thermal Gencos in Day-Ahead Markets

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modeled by variable costs, start-up costs and technical operating constraints, such as: ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, aiming to maximize the expected profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

Bidding Decision of Wind-Thermal GenCo in Day-Ahead Market

This paper deals with the self-scheduling problem of a price-taker having wind and thermal power production and assisted by a cyber-physical system for supporting management decisions in a day-ahead electric energy market. The self-scheduling is regarded as a stochastic mixed-integer linear programming problem. Uncertainties on electricity price and wind power are considered through a set of scenarios. Thermal units are modelled by start-up and variable costs, furthermore constraints are considered, such as: ramp up/down and minimum up/down time limits. The stochastic mixed-integer linear programming problem allows a decision support for strategies advantaging from an effective wind and thermal mixed bidding. A case study is presented using data from the Iberian electricity market.

Bidding strategy of wind-thermal energy producers

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

Modelo de otimização do espaço livre de armazenagem num silo de cereais

Este trabalho baseia-se num caso de estudo real de planeamento de operações de armazenagem num silo rural de cereais, e enquadra-se nos problemas de planeamento e programação de armazéns. Os programadores deparam-se diariamente com o problema de arranjar a melhor solução de transferência entre células de armazenagem, tentando maximizar o número de células vazias, por forma a ter maior capacidade para receber novos lotes, respeitando as restrições de receção e expedição, e as restrições de capacidade das linhas de transporte. Foi desenvolvido um modelo matemático de programação linear inteira mista e uma aplicação em Excel, com recurso ao VBA, para a sua implementação. Esta implementação abrangeu todo o processo relativo à atividade em causa, isto é, vai desde a recolha de dados, seu tratamento e análise, até à solução final de distribuição dos vários produtos pelas várias células. Os resultados obtidos mostram que o modelo otimiza o número de células vazias, tendo em conta os produtos que estão armazenados mais os que estão para ser rececionados e expedidos, em tempo computacional inferior a 60 segundos, constituindo, assim, uma importante mais valia para a empresa em causa.

A new MILP based approach for unit commitment in power production planning

This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

Esclonamento de máquinas de cogeração utilzando programação inteira mista

As centrais termoelétricas convencionais convertem apenas parte do combustível consumido na produção de energia elétrica, sendo que outra parte resulta em perdas sob a forma de calor. Neste sentido, surgiram as unidades de cogeração, ou Combined Heat and Power (CHP), que permitem reaproveitar a energia dissipada sob a forma de energia térmica e disponibilizá-la, em conjunto com a energia elétrica gerada, para consumo doméstico ou industrial, tornando-as mais eficientes que as unidades convencionais Os custos de produção de energia elétrica e de calor das unidades CHP são representados por uma função não-linear e apresentam uma região de operação admissível que pode ser convexa ou não-convexa, dependendo das caraterísticas de cada unidade. Por estas razões, a modelação de unidades CHP no âmbito do escalonamento de geradores elétricos (na literatura inglesa Unit Commitment Problem (UCP)) tem especial relevância para as empresas que possuem, também, este tipo de unidades. Estas empresas têm como objetivo definir, entre as unidades CHP e as unidades que apenas geram energia elétrica ou calor, quais devem ser ligadas e os respetivos níveis de produção para satisfazer a procura de energia elétrica e de calor a um custo mínimo. Neste documento são propostos dois modelos de programação inteira mista para o UCP com inclusão de unidades de cogeração: um modelo não-linear que inclui a função real de custo de produção das unidades CHP e um modelo que propõe uma linearização da referida função baseada na combinação convexa de um número pré-definido de pontos extremos. Em ambos os modelos a região de operação admissível não-convexa é modelada através da divisão desta àrea em duas àreas convexas distintas. Testes computacionais efetuados com ambos os modelos para várias instâncias permitiram verificar a eficiência do modelo linear proposto. Este modelo permitiu obter as soluções ótimas do modelo não-linear com tempos computationais significativamente menores. Para além disso, ambos os modelos foram testados com e sem a inclusão de restrições de tomada e deslastre de carga, permitindo concluir que este tipo de restrições aumenta a complexidade do problema sendo que o tempo computacional exigido para a resolução do mesmo cresce significativamente.

Three mathematical models for bucking-to-order

Abstract