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Reaction network flux analysis: Optimization-based evaluation of reaction pathways for biorenewables processing

AICHE JOURNAL 2012年第6期58卷 1788-1801页

作者： Voll, A. Marquardt, W. Rhein Westfal TH Aachen D-52064 Aachen Germany

Even though biomass is attracting increasing interest as a raw material in the chemical and the fuel industries, only few biobased production processes are yet established. At the same time a lot of new catalytic routes are proposed, but their potential in biorefinery applications is hard to predict. Reaction network flux analysis (RNFA) is introduced as a novel, rapid screening method which bridges the gap between chemo- or biocatalysis and process design by (1) systematically identifying and (2) subsequently analyzing and ranking the large number of alternative reaction pathways based on limited data. This optimization-based method helps to detect promising production routes as well as bottlenecks in possible pathways. The potential and the application of the RNFA methodology will be demonstrated by means of a case study for the production of the potential biofuel 3-methyl-tetrahydrofuran (3-MTHF) from the platform chemical itaconic acid (IA). (C) 2011 American Institute of Chemical Engineers AIChE J, 58: 17881801, 2012

关键词： reaction network flux analysis chemical process design biorenewables processing mixed-integer programming bioeconomy science

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The Benders Dual Decomposition Method

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OPERATIONS RESEARCH 2020年第3期68卷 878-895页

作者： Rahmaniani, Ragheb Ahmed, Shabbir Crainic, Teodor Gabriel Gendreau, Michel Rei, Walter Optimized Markets Inc Pittsburgh PA 15213 USA Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA Univ Quebec Montreal CIRRELT Montreal PQ H3C 3P8 Canada Univ Quebec Montreal Sch Management Ecole Sci Gest Montreal PQ H3C 3P8 Canada Ecole Polytech Montreal CIRRELT Montreal PQ H3C 3A7 Canada Ecole Polytech Montreal Dept Math & Ind Engn Montreal PQ H3C 3A7 Canada

Many methods that have been proposed to solve large-scale mixed integer linear programing (MILP) problems rely on decomposition techniques. These methods exploit either the primal or the dual structure of the problem, yielding the Benders decomposition or Lagrangian dual decomposition methods. We propose a new and high-performance approach, called Benders dual decomposition (BDD), which combines the complementary advantages of both methods. The development of BDD is based on a specific reformulation of the Benders subproblem, where local copies of the master variables are introduced in the proposed subproblem formulation and then priced out into the objective function. We show that this method (i) generates stronger feasibility and optimality cuts compared with the classical Benders method, (ii) can converge to the optimal integer solution at the root node of the Benders master problem, and (iii) is capable of generating high-quality incumbent solutions at the early iterations of the algorithm. We report encouraging computational results on various benchmark MILP problems.

关键词： Benders decomposition Lagrangian relaxation dual decomposition mixed-integer programming

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Scheduling of space to ground quantum key distribution

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EPJ QUANTUM TECHNOLOGY 2020年第1期7卷 1-34页

作者： Polnik, Mateusz Mazzarella, Luca Di Carlo, Marilena Oi, Daniel K. L. Riccardi, Annalisa Arulselvan, Ashwin Univ Strathclyde Dept Mech & Aerosp Engn Glasgow Lanark Scotland Univ Strathclyde SUPA Dept Phys Glasgow Lanark Scotland Univ Strathclyde Strathclyde Business Sch Glasgow Lanark Scotland

Satellite-based platforms are currently the only feasible way of achieving intercontinental range for quantum communication, enabling thus the future global quantum internet. Recent demonstrations by the Chinese spacecraft Micius have spurred an international space race and enormous interest in the development of both scientific and commercial systems. Research efforts so far have concentrated upon in-orbit demonstrations involving a single satellite and one or two ground stations. Ultimately satellite quantum key distribution should enable secure network communication between multiple nodes, which requires efficient scheduling of communication with the set of ground stations. Here we present a study of how satellite quantum key distribution can service many ground stations taking into account realistic constraints such as geography, operational hours, and most importantly, weather conditions. The objective is to maximise the number of keys a set of ground stations located in the United Kingdom could share while simultaneously reflecting the communication needs of each node and its relevance in the network. The problem is formulated as a mixed-integer linear optimisation program and solved to a desired optimality gap using a state of the art solver. The approach is presented using a simulation run throughout six years to investigate the total number of keys that can be sent to ground stations.

关键词： Quantum Key Distribution mixed-integer programming Scheduling Satellite Space Networking

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The integer approximation error in mixed-integer optimal control

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MATHEMATICAL programming 2012年第1-2期133卷 1-23页

作者： Sager, Sebastian Bock, Hans Georg Diehl, Moritz Heidelberg Univ Interdisciplinary Ctr Sci Comp Heidelberg Germany Katholieke Univ Leuven Optimizat Engn Ctr Louvain Belgium

We extend recent work on nonlinear optimal control problems with integer restrictions on some of the control functions (mixed-integer optimal control problems, MIOCP). We improve a theorem (Sager et al. in Math Program 118(1): 109-149, 2009) that states that the solution of a relaxed and convexified problem can be approximated with arbitrary precision by a solution fulfilling the integer requirements. Unlike in previous publications the new proof avoids the usage of the Krein-Milman theorem, which is undesirable as it only states the existence of a solution that may switch infinitely often. We present a constructive way to obtain an integer solution with a guaranteed bound on the performance loss in polynomial time. We prove that this bound depends linearly on the control discretization grid. A numerical benchmark example illustrates the procedure. As a byproduct, we obtain an estimate of the Hausdorff distance between reachable sets. We improve the approximation order to linear grid size instead of the previously known result with order (Hackl in Reachable sets, control sets and their computation, augsburger mathematisch-naturwissenschaftliche schriften. Dr. Bernd Winer, Augsburg, 1996). We are able to include a Special Ordered Set condition which will allow for a transfer of the results to a more general, multi-dimensional and nonlinear case compared to the Theorems in Pietrus and Veliov in (Syst Control Lett 58:395-399, 2009).

关键词： Optimal control mixed-integer programming Hybrid systems

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Promoting impulse buying by allocating retail shelf space to grouped product categories

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2016年第7期67卷 953-969页

作者： Flamand, Tulay Ghoniem, Ahmed Maddah, Bacel Univ Massachusetts Amherst MA 01003 USA Amer Univ Beirut Beirut Lebanon

This paper addresses a problem where a retailer seeks to optimize store-wide shelf-space allocation in order to maximize the visibility of products to consumers and consequently stimulate impulse buying. We consider a setting where the retailer, because of product affinities or the retailer's historical practice, has pre-clustered product categories into groups each of which must be assigned to a shelf. On the basis of its location in the store layout, each shelf is partitioned into contiguous shelf segments having different anticipated customer traffic densities. The retailer seeks to assign each group of product categories to a shelf, to determine the relative location of product categories within their assigned shelf, and to specify their allocated total shelf space within given lower/upper bounds. We propose a 0-1 integer programme that takes into account expected customer traffic densities within the store, groups of product categories, their relative profitability, and the desirability to keep certain product groups in the same aisle, with the objective of maximizing the impulse buying profit. The proposed model is grounded in a preprocessing scheme that explores feasible assignments of subsets of product groups to available aisles by iteratively solving an NP-hard subproblem and is numerically observed to greatly outperform an alternative mixed-integer programming formulation. We demonstrate the usefulness of and the enhanced tractability achieved by the proposed approach using a case study motivated by a grocery store in New England and a variety of simulated problem instances.

关键词： Shelf-space allocation impulse buying product shelf visibility mixed-integer programming optimization and modelling

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Column-Generation Framework of Nonlinear Similarity Model for Reconstructing Sibling Groups

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INFORMS JOURNAL ON COMPUTING 2015年第1期27卷 35-47页

作者： Chou, Chun-An Liang, Zhe Chaovalitwongse, Wanpracha Art Berger-Wolf, Tanya Y. DasGupta, Bhaskar Sheikh, Saad Ashley, Mary V. Caballero, Isabel C. SUNY Dept Syst Sci & Ind Engn Vestal NY 13902 USA Tongji Univ Sch Econ & Management Shanghai 20092 Peoples R China Univ Washington Dept Ind & Syst Engn & Radiol Seattle WA 98195 USA Univ Illinois Dept Comp Sci Chicago IL 60607 USA Univ Illinois Dept Biol Sci Chicago IL 60607 USA

Establishing family relationships, such as parentage and sibling relationships, is fundamental in biological research, especially in wild species, as they are often important to understanding evolutionary, ecological, and behavioral processes. Because it is commonly impossible to determine familial relationships from field observations alone, the reconstruction of sibling relationships often depends on informative genetic markers coupled with accurate sibling reconstruction algorithms. Most studies in the literature reconstruct sibling relationships using methods that are based on either statistical analyses (i.e., likelihood estimation) or combinatorial concepts (i.e., Mendelian inheritance laws) of genetic data. We present a novel computational framework that integrates both combinatorial concepts and statistical analyses into one sibling reconstruction optimization model. To solve this integrated model, we propose a column-generation approach with a branch-and-price method. Under the assumption of parsimonious reconstruction, the master problem is to find the minimum set of sibling groups to cover the tested population. Pricing subproblems, which include both statistical similarity and combinatorial concepts of genetic data, are iteratively solved to generate high-quality sibling group candidates. Tested on real biological data sets, our approach efficiently provides reconstruction results that are more accurate than those provided by other state-of-the-art reconstruction algorithms.

关键词： column generation branch and price set-covering problem mixed-integer programming computational biology sibling reconstruction

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Introducing approximate well dynamics into production optimization for operations scheduling

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COMPUTERS & CHEMICAL ENGINEERING 2020年 136卷 106773-000页

作者： Hulse, Eduardo Otte Silva, Thiago Lima Camponogara, Eduardo Rosa, Vinicius Ramos Vieira, Bruno Ferreira Teixeira, Alex Furtado Univ Fed Santa Catarina Dept Automat & Syst Engn CxP 476 BR-88040900 Florianopolis SC Brazil NTNU Dept Geosci & Petr N-7031 Trondheim Norway Petroleo Brasileiro SA BR-20031912 Rio De Janeiro RJ Brazil Petrobras Res Ctr BR-21949900 Rio De Janeiro RJ Brazil

Most of the literature on short-term production optimization concerns the computation of optimal system settings for steady-state operations. Such methodologies are applicable when the scales of time are faster than reservoir dynamics, and slower than the dynamics of top-side equipment. Effectively static problems are solved over time in response to changes in the prevailing conditions, which will remain persistent for long periods. However, when platform conditions change frequently or suddenly possibly due to reduced processing capacity, the dynamics of wells should not be neglected and well operations should be scheduled over time. To this end, this paper proposes a novel mathematical formulation for production optimization when dynamics matters, specifically when wells are shut-in (due to processing capacity drops) and restarted later as the normal conditions are recovered. The effectiveness of the methodology to schedule well operations is assessed by simulation of synthetic and field cases involving an offshore production platform. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Short-term production optimization Startup well operation Approximate well dynamics mixed-integer programming

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Aircraft routing with generalized maintenance constraints

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2018年 80卷 111-122页

作者： Safaei, Nima Jardine, Andrew K. S. Scotiabank Data Sci & Analyt 40 King St W Toronto ON M5H 1H1 Canada Univ Toronto Dept Mech & Ind Engn 5 Kings Coll Rd Toronto ON M5S 3G8 Canada

The literature on aircraft maintenance routing generally ignores the full range of maintenance requirements by only considering the most frequent maintenance type. The range of maintenance types and variety of individual aircraft's ages and utilization rates means the maintenance demand for each aircraft differs from one period to another, thus complicating aircraft routing decisions. This study proposes a new formulation of the aircraft maintenance routing problem in which maintenance requirements are built as generalized capacity constraints, ensuring sufficient maintenance opportunities are available within the planned routes to satisfy the maintenance demands of individual aircraft. Our new approach suggests minimizing maintenance misalignment using an interactive mechanism between aircraft routing and maintenance planning decisions. The computational results using real datasets reveal continuous reduction and convergence in maintenance misalignment through the proposed interactive mechanism. The lack of an effective interaction between the abovementioned decisions significantly increases the maintenance misalignment costs. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Aircraft routing Capacity constraints Maintenance mixed-integer programming

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Γ-robust optimization of project scheduling problems

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COMPUTERS & OPERATIONS RESEARCH 2024年 161卷

作者： Koster, Arie M. C. A. Segschneider, Jenny Ventsch, Nicole Rhein Westfal TH Aachen Res Area Discrete Optimizat Pontdriesch 10-12 D-52056 Aachen Germany

In this paper, we investigate the problem of finding a robust baseline schedule for the project scheduling problem under uncertain process times. We assume that the probability distribution for the duration is unknown, but an estimate is given along with an interval in which this time can vary. At most Gamma of the tasks will deviate from the estimated time. We present two approaches to solving this problem. The first approach treats the problem of determining the earliest guaranteed finish times and can be solved in polynomial time by an extension of the critical path method. The second is a two-stage approach that determines the baseline schedule in the first stage and an adaptation to the scenario in the second stage. We show strong NP-hardness of the second stage problem and introduce a novel formulation. From this formulation we derive an exact algorithm and three heuristics. A computational study on benchmark instances shows that the heuristics perform well on larger instances.

关键词： Robust project scheduling Budgeted uncertainty Two-stage robust optimization Heuristics mixed-integer programming

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Intelligent decision modeling for optimizing railway cold chain service networks under uncertainty

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INFORMATION SCIENCES 2024年 679卷

作者： Gan, Mi Li, Dandan Yao, Zhu Yu, Hao Ou, Qichen Southwest Jiaotong Univ Sch Transportat & Logist Chengdu Peoples R China Southwest Jiaotong Univ Natl Engn Lab Integrated Transportat Big Data Appl Chengdu Peoples R China UiT Arctic Univ Norway Dept Ind Engn Narvik Norway

Railway cold chain service network design (RCC-SND) aims to optimize the utilization of stations and lines as well as train allocations in a manner that minimizes costs while satisfying the service requirements of shippers. Furthermore, the uncertainties associated with freight demand, transportation costs, quality loss, station handling capacity, and arc capacity make the RCC-SND a complex decision-making problem. To tackle this challenge, we first formulate a mixed-integer Nonlinear programming (MINLP) model to determine hub locations, freight wagon flows, and service frequency. To cope with uncertain parameters with varying degrees of uncertainty incorporated in the model, we extend the problem using fuzzy programming and further convert it to its crisp counterpart. A real-world cases study in Southwest China is performed to validate the proposed model, whose results provide different strategies for decision-makers with varying preferences. There are some main findings: As the number of hubs increases from 5 to 6, a maximum total cost savings of 1.99% can be achieved. Railway operators may opt for different decision preferences, for decisions prioritizing economic efficiency, the cost can decrease by 2.69% compared to deterministic optimization.

关键词： Railway cold chain Service network design Uncertainty Fuzzy sets mixed-integer programming

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