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Multi-objective short-term production scheduling for open-pit mines: a hierarchical decomposition-based algorithm

ENGINEERING OPTIMIZATION 2018年第12期50卷 2143-2160页

作者： Blom, Michelle Pearce, Adrian R. Stuckey, Peter J. Univ Melbourne Sch Comp & Informat Syst Melbourne Vic Australia

This article presents a novel algorithm for solving a short-term open-pit production-scheduling problem in which several objectives, of varying priority, characterize the quality of each solution. A popular approach employs receding horizon control, dividing the horizon into N period-aggregates of increasing size (number of periods or span). An N-period mixed integer program (MIP) is solved for each period in the original horizon to incrementally construct a production schedule one period at a time. This article presents a new algorithm that, in contrast, decomposes the horizon into N period-aggregates of equal size. Given a schedule for these N periods, obtained by solving an N-period MIP, the first of these aggregates is itself decomposed into an N-period scheduling problem with guidance provided on what regions of the mine should be extracted. The performance of this hierarchical decomposition-based approach is compared with that of receding horizon control on a suite of data sets generated from an operating mine producing millions of tons of ore annually. As the number of objectives being optimized increases, the hierarchical decomposition-based algorithm outperforms receding horizon control, in a majority of instances.

关键词： Short-term open-pit production scheduling mixed-integer programming hierarchical decomposition

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Hybrid Approach to Construction Project Risk Management with Simultaneous FMEA/ISO 31000/Evolutionary Algorithms: Empirical Optimization Study

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JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT 2018年第6期144卷

作者： Rahimi, Yaser Tavakkoli-Moghaddam, Reza Iranmanesh, Seyed Hossein Vaez-Alaei, Maliheh Univ Tehran Sch Ind Engn Coll Engn Tehran *** Iran

Uncertainty and risks have been the inherent characteristics of large-scale projects. Although practitioners have applied different project risk management standards, numerous uncertainties, and risks in large-scale construction projects have led to significant failures in fulfilling a project's goals. Therefore, in this study, a hybrid approach based on failure mode effects analysis (FMEA)/ISO 31000 has been proposed to identify, evaluate, and control the problem effectively. This hybrid approach is not a very accurate approach in providing an appropriate risk response;hence, a mixed-integer programming (MIP) model has been proposed to select the optimized risk response strategies for the project. In the present study, a model based on synergies among project risk responses was developed that is capable of considering the various criteria in the objective function and optimizing them based on the defined projects. Risk response selection for a large-scale project is a complex problem. Because of the nondeterministic polynomial time (NP)-hardness of the presented model, two metaheuristic algorithms, namely, the self-adaptive imperialist competitive algorithm and invasive weed optimization, were developed to solve the proposed MIP model. A large-scale high-rise residential building was evaluated as a case study to investigate the model proposed in this study empirically.

关键词： Risk management Risk response strategy mixed-integer programming Evolutionary algorithms

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ParaXpress: an experimental extension of the FICO Xpress-Optimizer to solve hard MIPs on supercomputers

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OPTIMIZATION METHODS & SOFTWARE 2018年第3期33卷 530-539页

作者： Shinano, Yuji Berthold, Timo Heinz, Stefan Zuse Inst Berlin Berlin Germany Fair Isaac Germany GmbH Berlin Germany

The Ubiquity Generator (UG) is a general framework for the external parallelization of mixed integer programming (MIP) solvers. In this paper, we present ParaXpress, a distributed memory parallelization of the powerful commercial MIP solver FICO Xpress. Besides sheer performance, an important feature of Xpress is that it provides an internal parallelization for shared memory systems. When aiming for a best possible performance of ParaXpress on a supercomputer, the question arises how to balance the internal Xpress parallelization and the external parallelization by UG against each other. We provide computational experiments to address this question and we show computational results for running ParaXpress on a Top500 supercomputer, using up to 43,344 cores in parallel.

关键词： mixed-integer programming distributed memory parallelization

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From feasibility to improvement to proof: three phases of solving mixed-integer programs

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OPTIMIZATION METHODS & SOFTWARE 2018年第3期33卷 499-517页

作者： Berthold, Timo Hendel, Gregor Koch, Thorsten Fair Isaac Germany GmbH Berlin Germany Zuse Inst Berlin Berlin Germany Queen Mary Univ London Sch Math Sci London England

Modern mixed-integer programming (MIP) solvers employ dozens of auxiliary algorithmic components to support the branch-and-bound search in finding and improving primal solutions and in strengthening the dual bound. Typically, all components are tuned to minimize the average running time to prove optimality. In this article, we take a different look at the run of a MIP solver. We argue that the solution process consists of three distinct phases, namely achieving feasibility, improving the incumbent solution, and proving optimality. We first show that the entire solving process can be improved by adapting the search strategy with respect to the phase-specific aims using different control tunings. Afterwards, we provide criteria to predict the transition between the individual phases and evaluate the performance impact of altering the algorithmic behaviour of the non-commercial MIP solver Scip at the predicted phase transition points.

关键词： optimization software mixed-integer programming branch-and-bound adaptive search behaviour optimality prediction

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A Bayesian framework for molecular strain identification from mixed diagnostic samples

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INVERSE PROBLEMS 2018年第10期34卷

作者： Mustonen, Lauri Gao, Xiangxi Santana, Asteroide Mitchell, Rebecca Vigfusson, Ymir Ruthotto, Lars Emory Univ Dept Math & Comp Sci 400 Dowman Dr Atlanta GA 30322 USA Georgia Inst Technol Sch Ind & Syst Engn 755 Ferst Dr Atlanta GA 30318 USA Emory Univ Nell Hodgson Woodruff Sch Nursing 1520 Clifton Rd Atlanta GA 30322 USA Reykjavik Univ Sch Comp Sci Menntavegi 1 IS-101 Reykjavik Iceland

We provide a mathematical formulation and develop a computational framework for identifying multiple strains of microorganisms from mixed samples of DNA. Our method is applicable in public health domains where efficient identification of pathogens is paramount, e.g. for the monitoring of disease outbreaks. We formulate strain identification as an inverse problem that aims at simultaneously estimating a binary matrix (encoding presence or absence of mutations in each strain) and a real-valued vector (representing the mixture of strains) such that their product is approximately equal to the measured data vector. The problem at hand has a similar structure to blind deconvolution, except for the presence of binary constraints, which we enforce in our approach. Following a Bayesian approach, we derive a posterior density. We present two computational methods for solving the non-convex maximum a posteriori estimation problem. The first one is a local optimization method that is made efficient and scalable by decoupling the problem into smaller independent subproblems, whereas the second one yields a global minimizer by converting the problem into a convex mixed-integer quadratic programming problem. The decoupling approach also provides an efficient way to integrate over the posterior. This provides useful information about the ambiguity of the underdetermined problem and, thus, the uncertainty associated with numerical solutions. We evaluate the potential and limitations of our framework in silico using synthetic and experimental data with available ground truths.

关键词： Bayesian inverse problems mixed-integer programming molecular biology

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Planning inland vessel operations in large seaports using a two-phase approach

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 106卷 41-57页

作者： Li, Shijie Negenborn, Rudy R. Lodewijks, Gabriel Delft Univ Technol Dept Maritime & Transport Technol Mekelweg 2 NL-2628 CD Delft Netherlands Wuhan Univ Technol Sch Logist Engn 1178 Heping Rd Wuhan Hunan Peoples R China

Inland vessels are often used to transport containers between large seaports and the hinterland. Each time a vessel arrives in such a port, it typically visits several terminals to load and unload containers. In the Port of Rotterdam, the largest port in Europe, there are 77,000 inland vessels that have moored in the port in 2014 for transporting cargo. With the significant growth of containerized cargo transportation over the last decade, large seaports are under pressure to ensure high handling efficiency. Due to this development and the limited capacity at terminals, the inland vessels usually spend longer time in the port that originally planned. This leads to low utilization of terminal resources and congestion in the port. This paper proposes a novel two-phase planning approach that could improve this, taking into account several practical constraints. Specifically, we take into account the restricted opening times of terminals, the priority of sea-going vessels, and the different terminal capacities and sizes. In addition, we also consider the option for inland vessels to carry out additional inter-terminal transport tasks. Our approach is based on the integration of mixed-integer programming (MIP) and constraint programming (CP) to generate rotation plans for inland vessels. In the first phase, a single vessel optimization problem is solved using MIP. In the second phase, a multiple vessel coordination problem is formulated using CP;three large neighborhood search (LNS)-based heuristics are proposed to solve the problem. Simulation experiments show that the proposed INS-based heuristic outperforms the performance obtained with a state-of-the-art commercial CP solvers both regarding the solution quality and the computation time. Moreover, the simulation results indicate significant improvements with shorter departure times, sojourn times and waiting times. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Vessel rotation planning mixed-integer programming Constraint programming

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Stochastic Security-Constrained Scheduling of Coordinated Electricity and Natural Gas Infrastructures

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IEEE SYSTEMS JOURNAL 2017年第3期11卷 1674-1683页

作者： Alabdulwahab, Ahmed Abusorrah, Abdullah Zhang, Xiaping Shahidehpour, Mohammad King Abdulaziz Univ Dept Elect Engn & Comp Engn Jeddah 21589 Saudi Arabia King Abdulaziz Univ Renewable Energy Res Grp Jeddah 21589 Saudi Arabia IIT Robert W Galvin Ctr Elect Innovat Chicago IL 60616 USA King Abdulaziz Univ Renewable Energy Res Grp Jeddah 22254 Saudi Arabia

This paper proposes a coordinated stochastic model for studying the interdependence of electricity and natural gas transmission networks (referred to as EGTran). The coordinated model incorporates the stochastic power system conditions into the solution of security-constrained unit commitment problem with natural gas network constraints. The stochastic model considers random outages of generating units and transmission lines, as well as hourly forecast errors of day-ahead electricity load. The Monte Carlo simulation is applied to create multiple scenarios for the simulation of the uncertainties in the EGTran model. The nonlinear natural gas network constraints are converted into linear constraints and incorporated into the stochastic model. Numerical tests are performed in a six-bus system with a seven-node gas transmission network and the IEEE 118-bus power system with a ten-node gas transmission network. Numerical results demonstrate the effectiveness of EGTran to analyze the impact of random contingencies on power system operations with natural gas network constraints. The proposed EGTran model could be utilized by grid operators for the short-term commitment and dispatch of power systems in highly interdependent conditions with relatively large natural gas-fired generating units.

关键词： Load forecasting mixed-integer programming natural gas and electricity infrastructures optimization stochastic security-constrained unit commitment (SCUC) uncertainty

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Cost-based feature selection for Support Vector Machines: An application in credit scoring

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第2期261卷 656-665页

作者： Maldonado, Sebastian Perez, Juan Bravo, Cristian Univ Los Andes Fac Ingn & Ciencias Aplicadas Monsenor Alvaro del Portillo 12455 Santiago Chile Univ Southampton Dept Decis Analyt & Risk Southampton Business Sch Univ Rd Southampton SO17 1BJ Hants England

In this work we propose two formulations based on Support Vector Machines for simultaneous classification and feature selection that explicitly incorporate attribute acquisition costs. This is a challenging task for two main reasons: the estimation of the acquisition costs is not straightforward and may depend on multivariate factors, and the inter-dependence between variables must be taken into account for the modelling process since companies usually acquire groups of related variables rather than acquiring them individually. mixed-integer linear programming models are proposed for constructing classifiers that constrain acquisition costs while classifying adequately. Experimental results using credit scoring datasets demonstrate the effectiveness of our methods in terms of predictive performance at a low cost compared to well-known feature selection approaches. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Analytics Feature selection Support Vector Machines mixed-integer programming Credit scoring

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Integrating financial planning, loaning strategies and project scheduling on a discrete-time model

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JOURNAL OF MANUFACTURING SYSTEMS 2017年 44卷 217-229页

作者： Martins, Pedro Polytech Inst Coimbra ISCAC Coimbra Portugal Univ Lisbon Fac Sci Ctr Math Fundamental Applicat & Operat Res CMAF C Lisbon Portugal

In spite of the large amount of work relating project scheduling and cash-flows, less attention has been given to borrowing strategies for supporting projects' costs. In many practical problems, loaning is not a choice but the unique option for initiating the process. In fact, an adequate loaning strategy is crucial, not just for launching the project but also for guaranteeing its financial success. In this work, we discuss project scheduling along a fixed horizon cash-flow stream that incorporates loaning strategies. There is an initial capital made available by the project owner (client), to be used to support the activities' costs, together with cash in-flows brought by loans. These loans are assumed to be fully amortized within the given time horizon. After completion, the activities start generating profits, feeding back the financial stream. In addition, the project is not forced to be fully implemented, in the sense that the activities are allowed not to perform, although assuming the precedence relationships imposed. So, the problem is to determine when to launch the elected activities such that the cash-flow at the end of the planning horizon is maximized. We propose a mixed integer linear programming model for the problem and discuss applications involving different environments and specificities. (C) 2017 Published by Elsevier Ltd on behalf of The Society of Manufacturing Engineers.

关键词： Discrete-time financial planning Project scheduling Loaning strategies mixed-integer programming

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Variable guidance for pedestrian evacuation considering congestion, hazard, and compliance behavior

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2017年 85卷 664-683页

作者： Chu, James-C. Chen, Albert Y. Lin, Yu-Fu Natl Taiwan Univ Dept Civil Engn Taipei Taiwan

A methodology for optimizing variable pedestrian evacuation guidance in buildings with convex polygonal interior spaces is proposed. The optimization of variable guidance is a bi-level problem. The calculation of variable guidance based on the prediction of congestion and hazards is the upper-level problem. The prediction of congestion provided the variable guidance is the lower-level problem. A local search procedure is developed to solve the problem. The proposed methodology has three major contributions. First, a logistic regression model for guidance compliance behavior is calibrated using a virtual reality experiment and the critical factors for the behavior are identified. Second, the guidance compliance and following behaviors are considered in the lower-level problem. Third, benchmarks are calculated to evaluate the performance of optimized variable guidance, including the lower bound of the maximum evacuation time and the maximum evacuation time under a fixed guidance. Finally, the proposed methodology is validated with numerical examples. Results show that the method has the potential to reduce evacuation time in emergencies.

关键词： Variable evacuation guidance Pedestrian simulation Congestion Guidance compliance Dynamic network mixed-integer programming

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