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作者： Shams-Shoaaee, Seyed Shervin McMaster University

学位级别：博士

With the rise of online retailer giants like Amazon, and enhancements in internet and mobile technologies, online shopping is becoming increasingly popular. This has lead to new opportunities in online price optimization. The overarching motivation and theme of this thesis is to review these opportunities and provide methods and models in the context of retailers' online pricing decisions. In Chapter 2 a multi-period revenue maximization and pricing optimization problem in the presence of reference prices is formulated as a mixed integer nonlinear program. Two algorithms are developed to solve the optimization problem: a generalized Benders' decomposition algorithm and a myopic heuristic. This is followed by numerical computations to illustrate the effciency of the solution approaches as well as some managerial pricing insights. In Chapter 3 a data-driven quadratic programming optimization model for online pricing in the presence of customer ratings is proposed. A new demand function is developed for a multi-product, nite horizon, online retail environment. To solve the optimization problem, a myopic pricing heuristic as well as exact solution approaches are introduced. Using customer reviews ratings data from ***, a new customer rating forecasting model is validated. This is followed by several analytical and numerical insights. In Chapter 4 a multinomial choice model is used for customer purchase decision to find optimal personalized price discounts for an online retailer that incorporates customer locations and feedback from their reviews. Closed form solutions are derived for two special cases of this problem. To gain some analytical insights extensive numerical experiments are carried followed by several analytical and numerical insights. Thesis Doctor of Philosophy (PhD) The increase in online retail and the improvements in mobile technologies has lead to advantages and opportunities for both customers and retailers. One of these advantages is the abi

关键词： Pricing Reference pricing mixed-integer nonlinear programming Generalized Benders' decomposition Customer rating e-commerce Quadratic programming Personalized price discounts nonlinear programming

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混合分离过程的有序设计框架(英文)

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Chinese Journal of Chemical Engineering 2008年第3期16卷 333-342页

作者： Wolfgang Marquardt Sven Kossack Korbinian Kraemer Process Systems Engineering and Center for Computational Engineering Science RWTH Aachen University

The design of optimal separation flow sheets for multi-component mixtures is still not a solved problem. This is especially the case when non-ideal or azeotropic mixtures or hybrid separation processes are considered. We review recent developments in this field and present a systematic framework for the design of separation flow sheets. This framework proposes a three-step approach. In the first step different flow sheets are generated. In the second step these alternative flow sheet structures are evaluated with shortcut methods. In the third step a rigorous mixed-integer nonlinear programming (MINLP) optimization of the entire flow sheet is executed to determine the best alternative. Since a number of alternative flow sheets have already been eliminated, only a few optimization runs are necessary in this final step. The whole framework thus allows the systematic generation and evaluation of separation processes and is illustrated with the case study of the separation of ethanol and water.

关键词： process synthesis distillation design rectification body method mixed-integer nonlinear programming

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A Framework for the Systematic Design of Hybrid Separation Processe

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Chinese Journal of Chemical Engineering 2008年第3期16卷 333-342页

作者： Wolfgang Marquardt Sven Kossack Korhjnian Kraemer Process Systems Engineering and Center for Computational Engineering Science RWTH Aachen University D-52064 Aachen Germany

The design of optimal separation flow sheets for multi-component mixtures is still not a solved problem This is especially the case when non-ideal or azeotropic mixtures or hybrid separation processes are considered. We review recent developments in this field and present a systematic framework for the design of separation flow sheets. This framework proposes a three-step approach. In the first step different flow sheets are generated. In the second step these alternative flow sheet structures are evaluated with shortcut methods. In the third step a rigorous mixed-integer nonlinear programming （MINLP） optimization of the entire flow sheet is executed to determine the best alternative. Since a number of alternative flow sheets have already been eliminated, only a few optimization runs are necessary in this final step. The whole framework thus allows the systematic generation and evaluation of separation processes and is illustrated with the case study of the separation of ethanol and water.

关键词： process synthesis distillation design rectification body method mixed-integer nonlinear programming

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Schedule Design for Liner Shipping Based on Wave Optimization 5

Schedule Design for Liner Shipping Based on Wave Optimizatio...

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5th International Conference on Transportation Engineering, ICTE 2015

作者： Xing, Jiangbo Zhong, Ming Transportation Management College Dalian Maritime University Dalian China

ISBN: (数字)9780784479384

ISBN: (纸本)9780784479384

This paper focuses on the schedule design problem for liner shipping to hedge against uncertainties. As a complement of Robust Optimization, a new optimization method-Wave Optimization (WO) is proposed, which is more suitable for socioeconomic systems. Then a mixed-integer nonlinear programming model based on WO is presented to solve the vessel schedule design problem. A real-life case study is investigated and proves that the proposed model could be solved effectively and efficiently for the realistic scale problem. © ASCE.

关键词： Liner shipping Schedule design Wave optimization mixed-integer nonlinear programming Liner shipping mixed integer linear programming design problems optimization method

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Brief Analysis of the Location and Determination of Maximum Capacity of Distributed Generation in Electrical Systems Considering Demand Scenarios in Ecuador

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ENERGIES 2024年第10期17卷 2308页

作者： De la Cruz, Roger David Tipan, Luis Fernando Cuji, Cristian Cristobal Univ Politecn Salesiana Engn Dept South CampusAve Rumichaca & Ave M Valverde Quito 170702 Ecuador

This research focuses on evaluating the importance of the use of renewable sources through distributed generation and its implication in the operation of electrical systems given that its incorporation has a direct impact on the expansion of the capacity of the networks, the minimization losses, and the impact on end users, all supported by the growth of demand. Under this context, the study focuses on incorporating distributed generation (DG), taking scenarios of base, medium, and peak demand and the modeling of the network, and subsequently evaluating the service quality indices and operating costs in addition to the electrical variables of the system. For this purpose, the present work proposes an optimization model to be solved using the Matlab (2021b) computational program together with GAMS (37.1.0 Major release (11 November 2021)) and mixed-integer nonlinear programming, determining the optimal insertion and determination of the maximum capacity of distributed generators while complying with the technical restrictions of the system and applying optimal AC power flows. Localizing and determining maximum capacity for distributed generation (DG) in electrical systems are critical aspects of modern grid planning and operation. With the increasing penetration of renewable energy sources and the growing complexity of energy demand patterns, efficient integration of DG has become paramount for ensuring grid reliability and sustainability. In this context, the analysis of DG localization and capacity determination considering demand scenarios emerges as a critical area of research in electrical engineering. By employing advanced optimization techniques such as mixed-integer nonlinear programming (MINP), this research addresses the multidimensional challenges associated with DG deployment, including technical constraints, economic considerations, and environmental impacts. Understanding the contribution of this optimization approach to electrical engineering is fundam

关键词： distributed power generation mixed-integer nonlinear programming power distribution networks power generation economics renewable energy sources

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Synthesis and optimization of an isothermal CSTR-network for the cyclohexane oxidation process

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COMPUTERS & CHEMICAL ENGINEERING 1996年第Sup1期20卷 S255-S260页

作者： Noronha, S Gruhn, G Department of Process and Plant Engineering Technical University Hamburg-Harburg Denickestr. 15 21073 Hamburg Germany

This paper deals with the synthesis and optimization of an isothermal CSTR-network for the industrially widespread cyclohexane oxidation process. Generally the mathematical representation of synthesis and optimization problems is attained by a superstructure, which considers all reasonable process topologies with respect to feasible connectivity options and alternative unit operations. integer variables indicating the selection of process units from the superstructure and nonlinear process constraints arising from the unit models and thermodynamic calculations lead to a mixed-integer nonlinear programming (MINLP) optimization problem. Here a new approach is introduced, where the corresponding MINLP optimization problem is handled by a commercial equation-oriented flowsheeting package in combination with a mixed-integer Linear programming (MILP) routine.

关键词： process synthesis process optimization mixed-integer nonlinear programming flowsheeting reactor network oxidation of cyclohexane

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On the mathematical modeling for optimal selecting of calibers of conductors in DC radial distribution networks: An MINLP approach

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ELECTRIC POWER SYSTEMS RESEARCH 2021年 194卷 107072-107072页

作者： Montoya, Oscar Danilo Gil-Gonzalez, Walter Grisales-Norena, Luis F. Univ Dist Francisco Jose de Caldas Fac Ingn Carrera 7 40B-53 Bogota 11021 DC Colombia Univ Tecnol Bolivar Lab Inteligente Energia Km 1 Via Turbaco Cartagena 131001 Colombia Inst Univ Pascual Bravo Fac Ingn Grp GIIEN Campus Robledo Medellin 050036 Colombia Inst Tecnol Metropolitan Dept Electromecan & Mecratron Medellin 050012 Colombia

This paper addresses the problem of optimal conductor selection in direct current (DC) distribution networks with radial topology. A nonlinear mixed-integer programming model (MINLP) is developed through a branch-to node incidence matrix. An important contribution is that the proposed MINLP model integrates a set of constraints related to the telescopic structure of the network, which allows reducing installation costs. The proposed model also includes a time-domain dependency that helps analyze the DC network under different load conditions, including renewable generation and battery energy storage systems, and different voltage regulation operative consigns. The objective function of the proposed model is made up of the total investment in conductors and the total cost of energy losses in one year of operation. These components of the objective function show multi-objective behavior. For this reason, different simulation scenarios are performed to identify their effects on the final grid configuration. An illustrative 10-nodes medium-voltage DC grid with 9 lines is used to carry out all the simulations through the General Algebraic Modeling System known as GAMS.

关键词： Direct current networks Medium-voltage distribution networks Radial structure Mathematical modeling mixed-integer nonlinear programming Telescopic configuration Optimal conductor selection

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Multi-mode resource-constrained project scheduling with uncertain activity cost

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 168卷 114475-114475页

作者： Xie, Fang Li, Haitao Xu, Zhe Shandong Technol & Business Univ Coll Finance Yantai 264005 Peoples R China Shandong Technol & Business Univ Collaborat Innovat Ctr Financial Serv Transformat Yantai 264005 Peoples R China Univ Missouri Coll Business Adm St Louis MO 63121 USA Beihang Univ Coll Econ & Management Beijing 100191 Peoples R China

The multi-mode resource-constrained project scheduling problem under uncertain activity cost (MRCPSP-UAC) has a wide range of applications in production planning and project management. We first build a new mixed integer nonlinear programming (MINLP) model with the objective of minimizing the risk of project cost overrun, which provides a vehicle to obtain optimal solutions. To overcome the computational challenge of exact method for solving large instances, we devise a construction heuristic (CH) with a multi-pass greedy improvement procedure to obtain a feasible solution efficiently. To further improve solution quality, a hybrid CH and genetic algorithm (CH-GA) is developed with a custom fitness function to properly calibrate the quality of an individual. A comprehensive computational study is performed to examine the impact of various problem parameters on the optimal solutions, and the performance of our algorithms. Our hybrid CH-GA performs well for large instances with significantly less computational time than the exact method.

关键词： Resource-constrained project scheduling Multi-mode Uncertain activity cost mixed-integer nonlinear programming Genetic algorithms

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CONTINUOUS AND mixed-integer programming SOLUTION OF A CHEMICAL PROCESS SYNTHESIS PROBLEM

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HUNGARIAN JOURNAL OF INDUSTRIAL CHEMISTRY 1991年第1期19卷 27-38页

作者： PIBOULEAU, L FLOQUET, P DOMENECH, S CNRS Toulouse France

In parallel to the increase of computer sophistication, optimization techniques are finding wide applications in chemical process design. The chemical process synthesis problem can be stated as a mixed-integer nonlinear programming problem, where the integer variables represent the process structure and the continuous variables refer to operating conditions of the process units. The formulation of a classical chemical engineering problem is presented in the first part on the paper. Three mathematical programming methods (GRG - branch and bound - and mixed-integer nonlinear programming) with increasing degree of sophistication are used to solve this problem, and the results are then compared. From this example, the mixed-integer nonlinear programming method appears to be the most powerful tool for solving chemical process synthesis problems, even though the branch and bound procedure is a well suitable approach for solving the particular problem of choosing configurations for a process. Finally it is shown that the introduction into the initial objective function of an outer penalty term on the number of process links may avoid equivalent process structures to be obtained.

关键词： nonlinear programming mixed-integer nonlinear programming BRANCH AND BOUND STRUCTURAL PARAMETERS PROCESS SYNTHESIS

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Reformulation, linearization, and decomposition techniques for balanced distributed operating room scheduling

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2020年第0期93卷 102043-000页

作者： Roshanaei, Vahid Luong, Curtiss Aleman, Dionne M. Urbach, David R. Univ Toronto Rotman Sch Management 105 St George Toronto ON M5S 3E6 Canada Univ Toronto Dept Mech & Ind Engn 5 Kings Coll Rd Toronto ON M5S 3G8 Canada Univ Toronto Inst Hlth Policy Management & Evaluat 155 Coll StSuite 425 Toronto ON M5S 3E3 Canada Univ Hlth Network Techna Inst 124-100 Coll St Toronto ON M5G 1P5 Canada Univ Hlth Network Toronto Gen Hosp Div Gen Surg 200 Elizabeth St Toronto ON M5G 2C4 Canada

We study the balanced distributed operating room (OR) scheduling (BDORS) problem as a location allocation model, encompassing two levels of balancing decisions: (i) daily macro imbalance among collaborating hospitals in terms of the number of allocated ORs and (ii) daily micro imbalance among open ORs in each hospital in terms of the total caseload assigned. BDORS is formulated as a novel mixed integer nonlinear programming (MINLP) in which the macro and micro imbalance are penalized using absolute value and quadratic functions. We develop various reformulation-linearization techniques (RLTs) for the MINLP models, leading to three mathematical modelling variants: (i) a mixed-integer quadratically constrained program (MIQCP) and (ii) two mixed-integer programs (MIPs) for the absolute value penalty function and an MIQCP for the quadratic penalty function. Two novel exact techniques based on reformulation-decomposition techniques (RDTs) are developed to solve these models: a uni- and a bi-level logic-based Benders decomposition (LBBD). We motivate the LBBD methods with an application to BDORS in the University Health Network (UHN), consisting of three collaborating hospitals: Toronto General Hospital, Toronto Western Hospital, and Princess Margaret Cancer Centre in Toronto, Ontario, Canada. The uni-level LBBD method decomposes the model into a surgical suite location, OR allocation, and macro balancing master problem (MP) and micro OR balancing sub-problems (SPs) for each hospital-day. The bi-level approach uses a relaxed MP, consisting of a surgical suite location and relaxed allocation/macro balancing MP and two optimization SPs. The primary SP is formulated as a bin-packing problem to allocate patients to open operating rooms to minimize the number of ORs, while the secondary SP is the uni-level micro balancing SP. Using UHN datasets consisting of two datasets, hard MP/easy SPs and easy MP/hard SPs, we show that both LBBD approaches and both MIP models solved via Gu

关键词： Healthcare Operating room scheduling Balanced location-allocation Large scale optimization Multi-level decomposition Logic-based Benders balancing cuts mixed-integer nonlinear programming

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