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13th conference on Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction

作者： Ji, Xiaoyan Lundgren, Joakim Wang, Chuan Dahl, Jan Grip, Carl-Erik Lulea Univ Technol Div Energy Engn S-97187 Lulea Sweden Swerea MEFOS AB PRISMA Ctr Proc Integrat Steelmaking S-97125 Lulea Sweden

ISBN: (纸本)9788895608051

A process integration model is developed based on mixed integer linear programming. the analysis is carried out using the reMIND software in combination with the commercial optimization software CPLEX. the steam production (heat recovery boiler, bark boiler and steam turbines) and the process steam consumers (digester, evaporation plant, bleaching plant as well as pulp dry machine and paper making machine) are modeled as separate modules and thereafter linked and are validated using the operation data from a pulp and paper mill in the Northern Sweden. the whole plant is simulated and initial optimization runs are performed in which the cost is to be minimized.

关键词： Steam turbines

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Decomposition based hybrid metaheuristics

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2015年第1期244卷 66-76页

作者： Raidl, Guenther R. Vienna Univ Technol Inst Comp Graph & Algorithms A-1040 Vienna Austria

Difficult combinatorial optimization problems coming from practice are nowadays often approached by hybrid metaheuristics that combine principles of classical metaheuristic techniques with advanced methods from fields like mathematical programming, dynamic programming, and constraint programming. If designed appropriately, such hybrids frequently outperform simpler "pure" approaches as they are able to exploit the underlying methods' individual advantages and benefit from synergy. this article starts with a general review of design patterns for hybrid approaches that have been successful on many occasions. More complex practical problems frequently have some special structure that might be exploited. In the field of mixed integer linear programming, three decomposition techniques are particularly well known for taking advantage of special structures: Lagrangian decomposition, Dantzig-Wolfe decomposition (column generation), and Benders' decomposition. It has been recognized that these concepts may also provide a very fruitful basis for effective hybrid metaheuristics. We review the basic principles of these decomposition techniques and discuss for each promising possibilities for combinations with metaheuristics. the approaches are illustrated with successful examples from literature. (C) 2014 Elsevier B.V. All rights reserved.

关键词： combinatorial optimization Metaheuristics Mixed integer programming Hybrid optimization approaches Decomposition techniques

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Data-based Predictive optimization for Byproduct Gas System in Steel Industry 13

Data-based Predictive optimization for Byproduct Gas System ...

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13th IEEE conference on Automation Science and Engineering (IEEE CASE)

作者： Zhao, Jun Sheng, Chunyang Wang, Wei Pedrycz, Witold Liu, Quanli Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2R3 Canada

ISBN: (纸本)9781509067817

In light of significant complexity of the byproduct gas system in steel industry (which limits an ability to establish its physics-based model), this study proposes a data-based predictive optimization (DPO) method to carry out real-time adjusting for the gas system. Two stages of the method, namely the prediction modeling and real-time optimization, are involved. At the prediction stage, the states of the optimized objectives, the consumption of the outsourcing natural gas and oil, the power generation and the tank levels, are forecasted based on a proposed mixed Gaussian kernel-based prediction intervals (PIs) construction model. the Jacobian matrix of this model is represented by a kernel matrix through derivation, which greatly facilitates the subsequent calculation. At the second stage, a rolling optimization based on a mathematical programming technique involving continuous and integer decision-making variables is developed via the prediction intervals.

关键词： byproduct gas system energy optimization data-based modeling prediction interval

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Designing optimization Problems with Diverse Solutions 1

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24th international conference on integer programming and combinatorial optimization (IPCO)

作者： Hanguir, Oussama Ma, Will Ryan, Christopher thomas Columbia Univ Ind Engn & Operat Res New York NY 10027 USA Columbia Univ Grad Sch Business New York NY 10027 USA Univ British Columbia UBC Sauder Sch Business Vancouver BC V6T 1Z2 Canada

ISBN: (数字)9783031327261

ISBN: (纸本)9783031327254;9783031327261

We consider the problem of designing a linear program that has diverse solutions as the right-hand side varies. this problem arises in video game settings where designers aim to have players use different "weapons" or "tactics" as they progress. We model this design question as a choice over the constraint matrix A and cost vector c to maximize the number of possible supports of unique optimal solutions (what we call "loadouts") of Linear Programs max{c(inverted perpendicular) x vertical bar Ax <= b, x >= 0} with nonnegative data considered over all resource vectors b. We provide an upper bound on the optimal number of loadouts and provide a family of constructions that have an asymptotically optimal number of loadouts. the upper bound is based on a connection between our problem and the study of triangulations of point sets arising from polyhedral combinatorics, and specifically the combinatorics of the cyclic polytope. Our asymptotically optimal construction also draws inspiration from the properties of the cyclic polytope.

关键词： linear programming triangulations diversity

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An introduction to empty lattice simplices 7th

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7th international conference on integer programming and combinatorial optimization (IPCO VII)

作者： Sebo, A CNRS Lab Leibniz IMAG Grenoble France Kyoto Univ Math Sci Res Inst Kyoto 60601 Japan

ISBN: (纸本)3540660194

We study simplices whose vertices lie on a lattice and have no other lattice points. Such 'empty lattice simplices' come up in the theory of integer programming, and in some combinatorial problems. they have been investigated in various contexts and under varying terminology by Reeve, White, Scarf, Kannan and Lovasz, Reznick, Kantor, Naase and Ziegler, etc. Can the 'emptiness' of lattice simplices be 'well-characterized' ? Is their 'lattice-width' small ? Do the integer points of the parallelepiped they generate have a particular structure ? the 'good characterization' of empty lattice simplices occurs to be open in general ! We provide a polynomial algorithm for deciding when a given integer 'knapsack' or 'partition' lattice simplex is empty. More generally, we ask for a characterization of linear inequalities satisfied by the lattice points of a lattice parallelepiped. We state a conjecture about such inequalities, prove it for n less than or equal to 4, and deduce several variants of classical results of Reeve, White and Scarf characterizing the emptiness of small dimensional lattice simplices. For instance, a three dimensional integer simplex is empty if and only if all its faces have width 1. Seemingly different characterizations can be easily proved from one another using the Hermite normal form. In fixed dimension the width of polytopes can be computed in polynomial time (see the simple integer programming formulation of Naase and Ziegler). We prove that it is already NP-complete to decide whether the width of a very special class of integer simplices is 1, and we also provide for every n greater than or equal to 3 a simple example of n-dimensional empty integer simplices of width n - 2, improving on earlier bounds.

关键词： integer programming

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Constraint integer programming:A new approach to integrate CP and MIP 1

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5th international conference on Integration of AI and OR Techniques in Constraint programming for combinatorial optimization Problems

作者： Achterberg, Tobias Berthold, Timo Koch, thorsten Wolter, Kati ILOG Deutschland Ober Eschbacher Str 109 D-61352 Bad Homburg Germany Zuse Inst Berlin D-14195 Berlin Germany

ISBN: (数字)9783540681557

ISBN: (纸本)9783540681540

this article introduces constraint integer programming (CIP), which is a novel way to combine constraint programming (CP) and mixed integer programming (MIP) methodologies. CIP is a generalization of MIP that supports the notion of general constraints as in CP. this approach is supported by the CIP framework SCIP, which also integrates techniques from SAT solving. SCIP is available in source code and free for non-commercial use. We demonstrate the usefulness of CIP on two tasks. First, we apply the constraint integer programming approach to pure mixed integer programs. Computational experiments show that SCIP is almost competitive to current state-of-the-art commercial MIP solvers. Second, we employ the CIP framework to solve chip design verification problems, which involve some highly non-linear constraint types that are very hard to handle by pure MIP solvers. the CIP approach is very effective here: it can apply the full sophisticated MIP machinery to the linear part of the problem, while dealing with the non-linear constraints by employing constraint programming techniques.

关键词： integer programming

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optimization Methods for the Partner Units Problem

Optimization Methods for the Partner Units Problem

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8th international conference on Integration of AI and OR Techniques in Constraint programming for combinatorial optimization Problems (CPAIOR)

作者： Aschinger, Markus Drescher, Conrad Friedrich, Gerhard Gottlob, Georg Jeavons, Peter Ryabokon, Anna thorstensen, Evgenij Univ Oxford Comp Lab Oxford OX1 2JD England Alpen Adria Univ Klagenfurt Inst Angewandte Informat Klagenfurt Austria

ISBN: (纸本)9783642213113

In this work we present the Partner Units Problem as a novel challenge for optimization methods. It captures a certain type of configuration problem that frequently occurs in industry. Unfortunately, it can be shown that in the most general case an optimization version of the problem is intractable. We present and evaluate encodings of the problem in the frameworks of answer set programming, propositional satisfiability testing, constraint solving, and integer programming. We also show how to adapt these encodings to a class of problem instances that we have recently shown to be tractable.

关键词： integer programming

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A Peak Power optimization Scheduling Algorithm for Multi-cycle Operation 13

A Peak Power Optimization Scheduling Algorithm for Multi-cyc...

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2016 13th IEEE international conference on Solid-State and Integrated Circuit Technology (ICSICT)

作者： Sun Qiang Computer and Information College Mudanjiang Normal University

ISBN: (纸本)9781467397209

this paper proposes a force-directed scheduling algorithm for peak power optimization based on multi-cycle operations. Utilizing the basic idea of traditional force-directed scheduling algorithm and resetting the parameters related to force, this new algorithm has realized the balanced distribution of cycle power in scheduling process, thus minimizing peak power. Experimental results show that with the same control step constraint and resource consumption, the algorithm proposed in this paper has been improved in the aspect of peak power optimization compared with traditional force-directed scheduling algorithms, and bears comparison with the integer linear programming method.

关键词： high-level synthesis force-directed scheduling peak power

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Constrained Discrete Black-Box optimization using Mixed-integer programming 39

Constrained Discrete Black-Box Optimization using Mixed-Inte...

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39th international conference on Machine Learning (ICML)

作者： Papalexopoulos, theodore P. Tjandraatmadja, Christian Anderson, Ross Vielma, Juan Pablo Belanger, David MIT Operat Res Ctr 77 Massachusetts Ave Cambridge MA 02139 USA Google Res Cambridge MA 02138 USA

Discrete black-box optimization problems are challenging for model-based optimization (MBO) algorithms, such as Bayesian optimization, due to the size of the search space and the need to satisfy combinatorial constraints. In particular, these methods require repeatedly solving a complex discrete global optimization problem in the inner loop, where popular heuristic inner-loop solvers introduce approximations and are difficult to adapt to combinatorial constraints. In response, we propose NN+MILP, a general discrete MBO framework using piecewise-linear neural networks as surrogate models and mixed-integer linear programming (MILP) to optimize the acquisition function. MILP provides optimality guarantees and a versatile declarative language for domain-specific constraints. We test our approach on a range of unconstrained and constrained problems, including DNA binding, constrained binary quadratic problems from the MINLPLib benchmark, and the NAS-Bench-101 neural architecture search benchmark. NN+MILP surpasses or matches the performance of black-box algorithms tailored to the constraints at hand, with global optimization of the acquisition problem running in a few minutes using only standard software packages and hardware.

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A Relax-and-Cut Framework for Gomory's Mixed-integer Cuts

A Relax-and-Cut Framework for Gomory's Mixed-Integer Cuts

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7th international conference Integration of AI and OR Techniques in Constraint programming for combinatorial optimization Problems

作者： Fischetti, Matteo Salvagnin, Domenico Univ Padua DEI I-35100 Padua Italy Univ Padua DMPA Padua Italy

ISBN: (纸本)9783642135194

Gomory's Mixed-integer Cuts (GMICs) are widely used in modern branch-and-cut codes for the solution of Mixed-integer Programs. Typically, GMICs are iteratively generated from the optimal basis of the current Linear programming (LP) relaxation, and immediately added to the LP before the next round of cuts is generated. Unfortunately, this approach prone to instability. In this paper we analyze a different scheme for the generation of rank-1 GMIC read from a basis of the original LP-the one before the addition of any cut. We adopt a relax-and-cut approach where the generated GMIC are not added to the current LP, but immediately relaxed in a Lagrangian fashion. Various elaborations of the basic idea are presented, that lead to very fast-yet accurate-variants of the basic scheme. Very encouraging computational results are presented, with a comparison with alternative techniques from the literature also aimed at improving the GMIC quality, including those proposed very recently by Balas and Bonami and by Dash and Goycoolea.

关键词： Mixed-integer programming Gomory's cuts Lagrangian relaxation Relax and Cut

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