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Optimal processing pathway for the production of biodiesel from microalgal biomass: A superstructure based approach

COMPUTERS & CHEMICAL ENGINEERING 2013年 58卷 305-314页

作者： Rizwan, Muhammad Lee, Jay H. Gani, Rafiqul Korea Adv Inst Sci & Technol Dept Chem & Biomol Engn Taejon 305701 South Korea Tech Univ Denmark Dept Chem & Biochem Engn CAPEC DK-2800 Lyngby Denmark

In this study, we propose a mixed integer nonlinear programming (MINLP) model for superstructure based optimization of biodiesel production from microalgal biomass. The proposed superstructure includes a number of major processing steps for the production of biodiesel from microalgal biomass, such as the harvesting of microalgal biomass, pretreatments including drying and cell disruption of harvested biomass, lipid extraction, transesterification, and post-transesterfication purification. The proposed model is used to find the optimal processing pathway among the large number of potential pathways that exist for the production of biodiesel from microalgae. The proposed methodology is tested by implementing on a specific case with different choices of objective functions. The MINLP model is implemented and solved in GAMS using a database built in Excel. The results from the optimization are analyzed and their significances are discussed. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Superstructure optimization Biodiesel Microalgae mixed integer nonlinear programming Biorefinery

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FiberSCIP-A Shared Memory Parallelization of SCIP

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INFORMS JOURNAL ON COMPUTING 2018年第1期30卷 11-30页

作者： Shinano, Yuji Heinz, Stefan Vigerske, Stefan Winkler, Michael Zuse Inst Berlin D-14195 Berlin Germany Fair Isaac Germany GmbH D-14195 Berlin Germany GAMS Software GmbH D-14195 Berlin Germany Gurobi GmbH D-14195 Berlin Germany

Recently, parallel computing environments have become significantly popular. In order to obtain the benefit of using parallel computing environments, we have to deploy our programs for these effectively. This paper focuses on a parallelization of SCIP (Solving Constraint integer Programs), which is a mixed-integer linear programming solver and constraint integer programming framework available in source code. There is a parallel extension of SCIP named ParaSCIP, which parallelizes SCIP on massively parallel distributed memory computing environments. This paper describes FiberSCIP, which is yet another parallel extension of SCIP to utilize multi-threaded parallel computation on shared memory computing environments, and has the following contributions: First, we present the basic concept of having two parallel extensions, and the relationship between them and the parallelization framework provided by UG (Ubiquity Generator), including an implementation of deterministic parallelization. Second, we discuss the difficulties in achieving a good performance that utilizes all resources on an actual computing environment, and the difficulties of performance evaluation of the parallel solvers. Third, we present away to evaluate the performance of new algorithms and parameter settings of the parallel extensions. Finally, we demonstrate the current performance of FiberSCIP for solving mixed-integer linear programs (MIPs) and mixed-integer nonlinear programs (MINLPs) in parallel.

关键词： parallel branch-and-bound deterministic parallelism constraint integer programming mixed integer programming mixed integer nonlinear programming SCIP MIP MINLP

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Distributed implementation of generation scheduling algorithm on interconnected power systems

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ENERGY CONVERSION AND MANAGEMENT 2011年第12期52卷 3457-3464页

作者： Chung, K. H. Kim, B. H. Hur, D. Kwangwoon Univ Dept Elect Engn Seoul 139701 South Korea Korea Electrotechnol Res Inst Uiwang City 437808 Gyeonggi Provin South Korea Hongik Univ Sch Elect & Elect Engn Seoul 121791 South Korea

The emphasis in this paper is on investigating a new generation scheduling algorithm for the interconnected power systems. In general, the generation scheduling problem formulated as a mixed integer nonlinear programming (MINLP) can be efficiently computed by the generalized Benders decomposition (GBD) technique which decouples an original problem into the master problem and subproblems to allow remarkably fast and accurate solutions of very large problems. In order to ferret out efficient inter-temporal optimal power flow subproblems, we will propose a regional decomposition framework based on auxiliary problem principle (APP). Obviously, this scheme can find the most economic dispatch (ED) schedule under the power transactions for a multi-utility system without the exchange of each utility's own private information and major disruption to existing ED or optimal power flow (OPF) constructed by individual utilities. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Auxiliary problem principle Benders decomposition Distributed optimal power flow Economic dispatch Generation scheduling Interconnected power system mixed integer nonlinear programming Unit commitment

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Maximizing a class of submodular utility functions with constraints

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MATHEMATICAL programming 2017年第1-2期162卷 145-164页

作者： Yu, Jiajin Ahmed, Shabbir Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA

Motivated by stochastic 0-1 integer programming problems with an expected utility objective, we study the mixed-integer nonlinear set: where N is a positive integer, is a concave function, are nonnegative vectors, d is a real number and B is a positive real number. We propose a family of inequalities for the convex hull of P by exploiting submodularity of the function over and the knapsack constraint . Computational effectiveness of the proposed inequalities within a branch-and-cut framework is illustrated using instances of an expected utility capital budgeting problem.

关键词： Submodularity Cutting planes Lifting mixed integer nonlinear programming Branch-and-cut

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A branch-and-price approach for the continuous multifacility monotone ordered median problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第1期306卷 105-126页

作者： Blanco, Victor Gazquez, Ricardo Ponce, Diego Puerto, Justo Univ Granada Inst Math IMAG Granada Spain Univ Granada Dept Quant Methods Econ & Business Granada Spain Univ Seville Inst Math IMUS Seville Spain Univ Seville Dept Stats & OR Seville Spain

In this paper, we address the Continuous Multifacility Monotone Ordered Median Problem. The goal of this problem is to locate p facilities in Rd minimizing a monotone ordered weighted median function of the distances between given demand points and its closest facility. We propose a new branch-and -price procedure for this problem, and three families of matheuristics based on: solving heuristically the pricer problem, aggregating the demand points, and discretizing the decision space. We give detailed discussions of the validity of the exact formulations and also specify the implementation details of all the solution procedures. Besides, we assess their performances in an extensive computational experience that shows the superiority of the branch-and-price approach over the compact formulation in medium-sized instances. To handle larger instances it is advisable to resort to the matheuristics that also report rather good results.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Combinatorial optimization Continuous location Ordered median problems mixed integer nonlinear programming Branch-and-price

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Solving Multistage mixed nonlinear Convex Stochastic Problems

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INFORMATICA 2016年第4期27卷 799-818页

作者： Mijangos, Eugenio Univ Basque Country UPV EHU Dept Appl Math & Stat & Operat Res Math POB 644 Leioa Bizkaia Spain

We present an algorithm to solve multistage stochastic convex problems, whose objective function and constraints are nonlinear. It is based on the twin-node-family concept involved in the Branch-and-Fix Coordination method. These problems have 0-1 mixed-integer and continuous variables in all the stages. The non-anticipativity constraints are satisfied by means of the twin-node family strategy. In this work to solve each nonlinear convex subproblem at each node we propose the solution of sequences of quadratic subproblems. Due to the convexity of the constraints we can approximate them by means of outer approximations. These methods have been implemented in C++ with the help of CPLEX 12.1, which only solves the quadratic approximations. The test problems have been randomly generated by using a C++ code developed by this author. Numerical experiments have been performed and its efficiency has been compared with that of a well-known code. Key words: stochastic programming, convex programming, branch and fix coordination, mixed integer nonlinear programming, quadratic programming, outer approximation.

关键词： stochastic programming convex programming branch and fix coordination mixed integer nonlinear programming quadratic programming outer approximation

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Covering a line segment with variable radius discs

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COMPUTERS & OPERATIONS RESEARCH 2009年第5期36卷 1423-1436页

作者： Agnetis, Alessandro Grande, Enrico Mirchandani, Pitu B. Pacifici, Andrea Univ Arizona ATLAS Ctr Tucson AZ 85721 USA Univ Siena Dipartimento Ingn Informaz I-53100 Siena Italy Univ Roma Tor Vergata Dipartimento Ingn Impresa I-00133 Rome Italy

The paper addresses the problem of locating sensors with a circular field of view so that it given line segment is under full Surveillance, which is termed as the disc covering problem on a line. The cost of each sensor includes a fixed component f, and a variable component that is a convex function of the diameter of the field-of-view area. When only one type of sensor or, in general. one type of disc, is available, then a simple polynomial algorithm solves the problem. When (here are different types of sensors, the problem becomes hard. A branch-and-bound algorithm as well as an efficient heuristic are developed for the special case in which the variable cost component of each sensor is proportional to the square of the measure of the field-of-view area. The heuristic very often obtains the optimal solution as shown in extensive computational testing.

关键词： Sensor location Network covering problems mixed integer nonlinear programming

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Reformulations in mathematical programming: automatic symmetry detection and exploitation

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MATHEMATICAL programming 2012年第1-2期131卷 273-304页

作者： Liberti, Leo Ecole Polytech LIX F-91128 Palaiseau France

If a mathematical program has many symmetric optima, solving it via Branch-and-Bound techniques often yields search trees of disproportionate sizes;thus, finding and exploiting symmetries is an important task. We propose a method for automatically finding the formulation group of any given mixed-integer nonlinear Program, and for reformulating the problem by means of static symmetry breaking constraints. The reformulated problem-which is likely to have fewer symmetric optima-can then be solved via standard Branch-and-Bound codes such as CPLEX (for linear programs) and Couenne (for nonlinear programs). Our computational results include formulation group tables for the MIPLib3, MIPLib2003, GlobalLib and MINLPLib instance libraries and solution tables for some instances in the aforementioned libraries.

关键词： Group Symmetry mixed integer nonlinear programming Branch and bound

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Hybrid MPC System for Platoon based Cooperative Lane change Control Using Machine Learning Aided Distributed Optimization

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2022年 159卷 104-142页

作者： Zhang, Hanyu Du, Lili Shen, Jinglai Univ Florida Dept Civil & Coastal Engn Gainesville FL 32608 USA Univ Maryland Dept Math & Stat Baltimore MD 21250 USA

This study is devoted to developing a platoon-based cooperative lane-change control (PB-CLC). It coordinates the trajectories of a CAV platoon under a platoon-centered platooning control to accommodate the CAV lane-change requests from its adjacent lane, aiming to reduce the negative traffic impacts on the platoon resulting from lane-change maneuvers, on the premise of ensuring CAVs' safety and mobility. Mathematically, the PB-CLC control is established using a hybrid model predictive control (MPC) system. The hybrid MPC system involves an MPC-based mixed integer nonlinear programming optimizer (MINLP-MPC) for optimal lane-change decisions, which considers multiple objectives such as traffic smoothness, driving comfort and lane-change response promptness subject to vehicle dynamics and safety constraints. To ensure the feasible lane-change, this study investigates and provides a lower bound of the lane-change time window by analyzing the MINLP-MPC model feasibility. Apart from the optimal lane-change decision consideration, the hybrid MPC system is well designed to ensure the control continuity and smoothness. In particular, the hybrid MPC system control feasibility and stability are proved to enable the platoon's back-and-forth state switchings between car-following and lane-change accommodation states. Next, we developed a machine learning aided distributed branch and bound algorithm (ML-DBB) to solve the MINLP-MPC model within a control sampling time interval (< 1 second). Specifically, built upon computer simulation and the c-LHS sampling technique, supervised machine learning models are developed offline to predict a reduced solution space of the integer variables, which is further integrated into the distributed branch and bound method to solve the MINLP-MPC model efficiently online. Extensive numerical experiments validate the effectiveness and applicability of the ML-DBB algorithm and the PB-CLC control.

关键词： connected and autonomous vehicles cooperative lane-change vehicle platooning model predictive control hybrid system controller mixed integer nonlinear programming supervised machine learning distributed branch and bound

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Global optimization of mass and property integration networks with in-plant property interceptors

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CHEMICAL ENGINEERING SCIENCE 2010年第15期65卷 4363-4377页

作者： Napoles-Rivera, Fabricio Maria Ponce-Ortega, Jose El-Halwagi, Mahmoud M. Jimenez-Gutierrez, Arturo Inst Tecnol Celaya Dept Chem Engn Celaya Gto Mexico Univ Michoacana Dept Chem Engn Morelia Mich Mexico Texas A&M Univ Dept Chem Engn College Stn TX 77843 USA

This paper presents a mathematical programming model for the optimal design of mass and property integration networks that include property interceptors with in the structure of the network, as opposed to the end-of-pipe use of such interceptors. The model is based on are cycle and reuse scheme that simultaneously satisfies process and environmental constraints. The properties considered in this work are composition, toxicity, theoretical oxygen demand, pH, density and viscosity. The property mixing rules included in the model give rise to bilinear terms for the property operators, and a global optimization algorithm is used for the solution of the model. The model minimizes the total annual cost of the network, which includes the fresh sources cost and the annualized property treatment system and the piping costs. Three examples are included to show the applicability and advantages of the proposed model. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Mass integration Property integration mixed integer nonlinear programming Mathematical modeling Optimization Chemical processes Design

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