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Optimal blending management of biomass resources used for biochemical conversion

BIOFUELS BIOPRODUCTS & BIOREFINING-BIOFPR 2018年第4期12卷 624-648页

作者： Roni, Mohammad S. Thompson, David Hartley, Damon Searcy, Erin Quang Nguyen Idaho Natl Lab Bioenergy Technol Dept Idaho Falls ID 83402 USA

This research develops an optimization model to describe the tradeoff among blend components in the least-cost biomass blend, based on resource availability, quality requirements, and logistics cost for a biochemical conversion. A mixed-integer linear programming model is developed to determine the least-cost blend from a set of candidate feedstocks. A case study - based on a biorefinery located in western Kansas that uses three-pass corn stover, two-pass corn stover, switchgrass, miscanthus, and municipal solid waste fractions to meet biochemical conversion specifications and feedstock demand - shows that the delivered cost of an optimal blend that meets carbohydrate and ash specifications is 12.12% higher than the delivered cost of optimal blend that meets a carbohydrate specification only. The results indicate that a least-cost blend that meets both carbohydrate and ash specifications consists of miscanthus (48.2%) and switchgrass (29.4%) whereas the least-cost blend meeting carbohydrate specification only comprises three-pass corn stover (55.4%) and two-pass corn stover (20.4%). An optimal blend uses a low-cost municipal solid waste fraction in all cases, implying that blending could be a potential strategy to reduce delivered feedstock cost. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

关键词： blending feedstock optimization biochemical conversion mixed-integer linear programming

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Flexible job shop scheduling with lot streaming and sublot size optimisation

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2018年第19期56卷 6391-6411页

作者： Bozek, Andrzej Werner, Frank Rzeszow Univ Technol Dept Comp & Control Engn Rzeszow Poland Otto Von Guericke Univ Inst Math Optimizat Magdeburg Germany

Models and optimisation approaches are developed for a flexible job shop scheduling problem with lot streaming and lot sizing of the variable sublots. A two-stage optimisation procedure is proposed. First, the makespan value is minimised with the smallest sublots defined for the problem instance. This makes it possible to shorten the makespan significantly, because each sublot is transferred separately to the next operation of a job. In the second stage, the sizes of the sublots are maximised without increasing the obtained makespan value. In this way, the quantity of sublots and transport activities is limited together with the related manufacturing cost. Two objectives are defined for the second stage. The first one is the maximisation of the sum of the sublot sizes of all operations, the second one is the maximisation of the number of the operations which do not need to be split at all. mixed-integer linear programming, constraint programming and graph-based models are implemented for the problem. Two optimisation approaches are developed and compared in computational experiments for each stage and objective, one approach is based on a third-party solver, and the second one on an independent own implementation, namely a tabu search and a greedy constructive heuristic.

关键词： flexible job shop lot streaming lot sizing mixed-integer linear programming tabu search constraint programming

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Modeling and Solving the Deadline Satisfaction Problem in Line-of-Balance Scheduling

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JOURNAL OF MANAGEMENT IN ENGINEERING 2018年第1期34卷

作者： Zou, Xin Zhang, Qian Zhang, Lihui North China Elect Power Univ Dept Econ Management Baoding 071003 Hebei Peoples R China North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China

This study investigates the deadline satisfaction problem in line-of-balance (LOB) scheduling, where each activity can be done concurrently in several units by hiring additional crews, and all employed crews are allocated to implement an activity in sequential units smoothly with no interruption. Furthermore, the project must be completed within a given deadline. In previous studies, the objective was to minimize the total number of crews under the assumption that the cost of hiring a crew is the same for all activities. In fact, this cost usually differs among activities because of the differences in type of work, crew size, and technical level of workers. This paper presents a mixed-integer linear programming model with an extended objective of minimizing the crew employment cost of all activities. The model is equipped with an exact procedure to validate the feasibility of a prespecified deadline. A highway project was used to show the application of the proposed method, and then extensive computational experiments were conducted to investigate the performance of the proposed method by comparing the obtained results with those obtained by the existing methods. The results highlight the significance of integrating the time-cost trade-off analysis, and indicate that the proposed method can find optimal solutions for large-scale projects within a reasonable amount of time.

关键词： Repetitive projects Line-of-balance Time-cost trade-off Deadline constraint mixed-integer linear programming

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Optimal wind farm cable routing: Modeling branches and offshore transformer modules

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NETWORKS 2018年第1期72卷 42-59页

作者： Fischetti, Martina Pisinger, David Vattenfall BA Wind Kolding Denmark Tech Univ Denmark Operat Res DTU Management Engn Produktionstorvet 424 DK-2800 Lyngby Denmark

Many EU countries aim at reducing fossil fuels in the near future, hence an efficient production of green energy is very important to reach this goal. In this article, we address the optimization of cable connections between turbines in an offshore wind park. Different versions of the problem have been studied in the recent literature. As turbines are becoming still more customized, it is important to be able to evaluate the impact of new technologies with a flexible optimization tool for scenario evaluation. In a previous joint project with Vattenfall BA Wind (a global leader in energy production) we have studied and modeled the main constraints arising in practical cases. Building on that model, in the present article, we address new technological features that have been recently proposed by Vattenfall's experts. We show how some new features can be modeled and solved using a mixed-integer linear programming paradigm. We report and discuss computational results on the performance of our new models on a set of real-world instances provided by Vattenfall.

关键词： computational analysis mixed-integer linear programming network models wind farm optimization

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Dynamic convexification within nested Benders decomposition using Lagrangian relaxation: An application to the strategic bidding problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第2期257卷 669-686页

作者： Steeger, Gregory Rebennack, Steffen Colorado Sch Mines Div Econ & Business Golden CO 80401 USA

Many decomposition algorithms like Benders decomposition and stochastic dual dynamic programming are limited to convex optimization problems. In this paper, we utilize a dynamic convexification method that makes use of Lagrangian relaxation to overcome this limitation and enables the modeling of non convex multi-stage problems using decomposition algorithms. Though the algorithm is confined by the duality gap of the problem being studied, the computed upper bounds (for maximization problems) are at least as good as those found via a linear programming relaxation approach. We apply the method to the strategic bidding problem for a hydroelectric producer, in which we ask: What is the revenue maximizing production schedule for a single price-maker hydroelectric producer in a deregulated, bid based market? Because the price-maker's future revenue function has a sawtooth shape, we model it using mixed-integer linear programming. To remedy the non-concavity issues associated with modeling the future revenue function as a mixed-integer linear program, we model the price-maker's bidding decision utilizing both Benders decomposition and Lagrangian relaxation. We demonstrate the utility of our algorithm through an illustrative example and through three case studies in which we model electricity markets in El Salvador, Honduras, and Nicaragua. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Lagrangian relaxation mixed-integer linear programming Benders decomposition Hydroelectric scheduling Strategic bidding problem Stochastic dual dynamic programming

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Analysis of Sparse Cutting Planes for Sparse MILPs with Applications to Stochastic MILPs

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MATHEMATICS OF OPERATIONS RESEARCH 2018年第1期43卷 304-332页

作者： Dey, Santanu S. Molinaro, Marco Wang, Qianyi Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA Pontifical Catholic Univ Rio de Janeiro Comp Sci Dept BR-22451 Rio De Janeiro Brazil

In this paper, we present an analysis of the strength of sparse cutting planes for mixed integer linear programs (MILP) with sparse formulations. We examine three kinds of problems: packing problems, covering problems, and more general MILPs with the only assumption that the objective function is nonnegative. Given an MILP instance of one of these three types, assume that we decide on the support of cutting planes to be used and the strongest inequalities on these supports are added to the linear programming relaxation. We present bounds on the ratio of optimal value of the LP relaxation after adding cuts and the optimal value of the MILP that depends only on the sparsity structure of the constraint matrix and the support of sparse cuts selected, that is, these bounds are completely data independent. These results also shed light on the strength of single-scenario cuts for two-stage stochastic MILPs.

关键词： cutting planes mixed-integer linear programming sparsity

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Optimal design of energy conversion units for residential buildings considering German market conditions

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ENERGY 2017年 139卷 895-915页

作者： Schuetz, Thomas Schraven, Markus Hans Remy, Sebastian Granacher, Julia Kemetmueller, Dominik Fuchs, Marcus Mueller, Dirk Rhein Westfal TH Aachen EON Energy Res Ctr Inst Energy Efficient Bldg & Indoor Climate Mathieustr 10 Aachen Germany

Many countries have passed governmental action plans to support the installation of renewable energy sources. However, most studies dealing with the optimization of building energy systems neglect a precise modeling of such subsidies, although these subsidies are specifically designed to strongly influence system setups. Therefore, this paper extends a model for the optimization of energy systems by a more accurate consideration of storage units and enhance both models by accounting for major German pieces of legislation aimed at supporting renewable energies. Additionally, we consider typical German market characteristics, in particular the availability of multiple gas and electricity tariffs. We compare our model with the original formulation regarding a pure cost minimization and a forced reduction of CO2 emissions for three new buildings located in Germany. The results imply that the considered subsidies strongly support the installation of PV modules and CHP units. Without these subsidies, batteries and solar thermal collectors become more important. Additionally, the findings illustrate that the new storage model is slightly more accurate, but only marginally affects the total annual costs and required computing times. The conducted sensitivity analysis has shown that the obtained results are relatively robust to variations in energy tariff costs and demands. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Building energy systems German regulations mixed-integer linear programming Multiple energy tariffs

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Bulk ship fleet renewal and deployment under uncertainty: A multi-stage stochastic programming approach

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2017年 97卷 69-96页

作者： Arslan, Ayse N. Papageorgiou, Dimitri J. Univ Florida Dept Ind & Syst Engn Gainesville FL 32611 USA ExxonMobil Res & Engn Co Corp Strateg Res 1545 Route 22 East Annandale NJ 08801 USA

Faced with simultaneous demand and charter cost uncertainty, an industrial shipping company must determine a suitable fleet size, mix, and deployment strategy to satisfy demand. It acquires vessels by time chartering and voyage chartering. Time chartered vessels are acquired for different durations, a decision made before stochastic parameters are known. Voyage charters are procured for a single voyage after uncertain parameters are realized. We introduce the first multi-stage stochastic programming model for the bulk ship fleet renewal problem and solve it in a rolling horizon fashion. Computational results indicate that our approach outperforms traditional methods relying on expected value forecasts. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Chartering Fleet planning Fleet renewal Maritime transportation mixed-integer linear programming Multi-stage stochastic programming

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A multi-objective model for the green capacitated location-routing problem considering environmental impact

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 110卷 114-125页

作者： Toro, Eliana M. Franco, John F. Granada Echeverri, Mauricio Guimaraes, Frederico Gadelha Univ Tecnol Pereira Fac Ingn Ind Pereira Colombia Univ Tecnol Pereira Fac Ingn Programa Ingn Elect Pereira Colombia Univ Estadual Paulista UNESP Ilha Solteira Brazil Univ Fed Minas Gerais Dept Elect Engn Belo Horizonte MG Brazil

The Capacitated Location-Routing Problem (CLRP) is a strategic-level problem involving the selection of one or many depots from a set of candidate locations and the planning of delivery routes from the selected depots to a set of customers. During the last few years, many logistics and operations research problems have been extended to include greenhouse effect issues and costs related to the environmental impact of industrial and transportation activities. In this paper a new mathematical model for the calculation of greenhouse gas emissions is developed and a new model for the CLRP considering fuel consumption minimization is proposed. This model, named Green CLRP (G-CLRP), is represented by a mixed integer linear problem, which is characterized by incorporating a set of new constraints focused on maintaining the problem connectivity requirements. The model proposed is formulated as a bi-objective problem, considering the minimization of operational costs and the minimization of environmental effects. A sensitivity analysis in instances of different sizes is done to show that the proposed objective functions are indeed conflicting goals. The proposed mathematical model is solved with the classical epsilon constraint technique. The results clearly show that the proposed model is able to generate a set of tradeoff solutions leading to interesting conclusions about the operational costs and the environmental impact. This set of solutions is useful in the decision process because several planning alternatives can be considered at strategic level. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Capacitated location-routing problem Green vehicle routing problem Green logistics mixed-integer linear programming Vehicle routing problem

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A new mixed-integer linear formulation for optimal placement of fault indicators in distribution systems

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2018年第12期28卷

作者： Derakhshandeh, Sayed Yaser Nikbakht, Mojtaba Shahrekord Univ Dept Engn Shahrekord Iran

In distribution systems, fault indicators (FIs) are used for fast faulted line-section location. Locations and the numbers of FIs affect the reliability indices of distribution companies and customers. This study presents a new linear method to find the optimum numbers and locations of FIs in distribution systems. Fault indicator placement of FIs is defined as an optimization problem whose aim is to improve the reliability indices with regard to the costs imposed on the system. The structure of the proposed formulation is mixed-integer linear programming. The proposed approach finds the optimal locations for FIs in such a way that customers' interruption cost and investment costs for the installation of FIs are minimized. The proposed formulation can be solved by using commercial solvers in a computational effective manner and rapidly converges to the global optimum. To evaluate the effectiveness of the proposed mixed-integer linear programming optimization formulation, several studies are presented and tested on bus number 4 of the reliability test system.

关键词： distribution system fault indicator mixed-integer linear programming optimal placement reliability

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