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Purchasing from multiple capital-constrained suppliers using order financing

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2024年第22期62卷 8157-8172页

作者： Wu, Andy Natl Chung Hsing Univ Dept Mkt 145 Xingda Rd Taichung 402 Taiwan

Small and medium enterprises (SMEs) play a critical role in supply chains and social stability. Unfortunately, SMEs often lack access to traditional bank financing. To develop SME suppliers, some creditworthy companies have built platforms to coordinate banks and suppliers by employing purchase order financing (POF). After noting that SMEs differ in terms of their operational flexibility and uncertainty, this research examines optimal purchasing portfolios on such platforms. Specifically, we construct a Stackelberg model involving one buyer and two suppliers and analyse the Karush-Kuhn-Tucker necessary conditions for a buyer's strategy upon which the optimal portfolio can be achieved. According to the experiments that we design to simulate about 200,000 various scenarios, the large buyer only needs to consider the top five strategies. The choice of strategy mainly depends on cost differences of suppliers, and flexibility can be used as an identifier of the purchase quantity.

关键词： Purchasing supply chain management OM-finance interface Stackelberg model non-linear programming purchase order financing

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Short-Term Hydrothermal Scheduling With Solar and Wind Farms Using Second-Order Cone Optimization With Chance-Box Constraints

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IEEE ACCESS 2021年 9卷 74095-74109页

作者： Camilo Castano, Juan Garces, Alejandro Fosso, Olav B. Univ Tecnol Pereira Dept Elect Power Engn Pereira 660003 Colombia Norwegian Univ Sci & Technol Dept Elect Power Engn N-7491 Trondheim Norway

Short-Term Hydrothermal Scheduling (STHS) is a classic problem in power system operation where the aim is to decide the dispatch of both thermal and hydroelectric units. This problem is complex due to its non-linear non-convex nature, and the requirements for fast solving for daily operation. Technologies such as wind and solar generation introduce stochastic behaviors, which have to be considered within the mathematical model. Although the problem is frequently solved by traditional and heuristic techniques, this paper proposes a new formulation based on convex approximations, and in particular, Second-Order Cone optimization, which addresses the nonlinear relation among water discharge, reservoir volume, and hydropower generation in a rigorous mathematical approach. Moreover, the impact of wind and solar generation on the power system is analyzed, modeling their stochastic behavior in a robust way by using chance-box constraints. Numerical results demonstrate that the Second-Order Cone approximation is precise and faster than techniques proposed recently and that the chance-box constraint approach guarantees a robust solution.

关键词： Hydroelectric power generation Stochastic processes programming Mathematical model Wind power generation Power systems Optimization Hydrothermal scheduling economic dispatch solar generation wind generation mathematical optimization non-linear programming chance-box constraints

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Resource-constrained project scheduling with concave processing rate functions

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2015年第5期66卷 794-806页

作者： Steeneek, Daniel W. Sarin, Subhash C. Virginia Tech Blacksburg VA 24061 USA

In this paper, we address a resource-constrained project scheduling problem involving a single resource. The resource can be applied at varying consumption rates to the activities of the project. The duration of each activity is defined by a convex, non-increasing time-resource trade-off function. In addition, activities are not preemptable (ie, the resource consumption rate of an activity cannot be altered while the activity is being processed). We explicitly consider variation of the rate at which an activity is performed with variation in resource consumption rate. We designate the number of units (amount of an activity) performed per unit time with variation in resource consumption rate as the processing rate function, and assume this function to be concave. We present a tree-search-based method in concert with the solution of a nonlinear program and the use of dominance properties to determine: (i) the sequence in which to perform the activities of the project, and (ii) the resource consumption rate to allocate to each activity so as to minimize the project duration (makespan). We also present results of an experimental investigation that reveal the efficacy of the proposed methodology Finally, we present an application of this methodology to a practical setting.

关键词： project scheduling project management mixed-integer programming non-linear programming

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Inventory policy and magazine reloading schedule optimisation for cutting tools in pipe manufacturing

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2022年第16期60卷 5029-5050页

作者： Hossain, Md Shahriar Jahan Sarker, Bhaba R. Northwestern State Univ Louisiana Dept Engn Technol 175 Sam Sibley Dr119-120 Williamson Hall Natchitoches LA 71497 USA Louisiana State Univ Dept Mech & Ind Engn Baton Rouge LA USA

In a steel pipe manufacturing industry, several machining centres are used for different purposes, where tool magazines speed up the tool exchange and machine setup. Early tool replacement incurs unutilised tool lives, leading to additional tool purchase. On the other hand, delays in tool replacement may result in sudden tool failure and machine breakdown. A multiple tool holding facility in a tool magazine provides a good opportunity to reduce the number of magazine reloading. However, an increased magazine size eventually leads to an increase in the inventory and operating cost for the tool magazine. To trade-off between the stated conflicting objectives, a non-linear mixed-integer programming problem is formulated to minimise the total cost for cutting tools. The problem is solved both optimally and heuristically to find an appropriate combination of tool ordering size, magazine size and reload timing. The throughput rate is observed to improve when an optimal size of tool magazine is installed. The sensitivity analyses are done to investigate the influence of different parameter(s) on the optimum solution.

关键词： Tool life non-linear programming inventory management replacement policies magazine reloading schedule

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The use of constrained and unconstrained optimization models in gradation design of hot mix asphalt mixture

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CONSTRUCTION AND BUILDING MATERIALS 2011年第1期25卷 115-122页

作者： Sivilevicius, Henrikas Podvezko, Valentinas Vakriniene, Sigute Vilnius Gediminas Tech Univ Dept Transport Technol Equipment LT-10105 Vilnius Lithuania Vilnius Gediminas Tech Univ Dept Math Stat LT-10223 Vilnius Lithuania

The paper describes the essential differences in determining optimal gradation of hot mix asphalt (HMA) mixture used in road building at the stages of its selection, initial design and production, and presents the respective algorithms. The models of constrained and unconstrained non-linear optimization are developed, allowing us to choose the best HMA mixture gradation based on mineral materials, whose gradation is known, when the total percent passing of HMA mixture aggregates is considered to be equally important for all sieves, or when preference is given to some of the sieves. A new linear optimization problem best suited for practical use due to its simplicity is offered. By introducing weight coefficients for the dimensions of the objective function of the model, zero deviations of the percent passing of HMA mixture aggregates from their standard values may be easily obtained, based on the preferences set. All mineral materials (aggregates) obtained at batch-type asphalt mixing plants should be used for HMA production. Their total mass is equal to unity, while the mass of each material is a positive quantity, and a predetermined relationship between the masses of imported filler and the reclaimed dust is used. In the experimental part of the work, the problems were solved using the SAS system. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： linear programming non-linear programming Unconstrained optimization Preference Hot mix asphalt (HMA) Gradation Percent passing Asphalt mixing plant (AMP) Mixtures

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Application of three-parameter Weibull mixture model for reliability assessment of NC machine tools: a case study

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2011年第C11期225卷 2718-2726页

作者： Wang, Z. Yang, J. Wang, G. Zhang, G. Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Chongqing Univ Adv Mfg Technol Lab Coll Mech Engn Chongqing 630044 Peoples R China

To analyse the reliability of numerical control (NC) machine tools, a three-parameter Weibull mixture model is proposed in this case study. Negative log-likelihood function is used as an optimal objective instead of solving complex system of equations;the problem of parameter estimation of mixture model is solved by a non-linear programming method. A comprehensive criteria, which include Akaike information criterion, Bayesian information criterion, and root mean squared error, is presented for selecting the number of components of mixture model. The field failure data of three NC machine tools are analysed and the results of reliability assessment, such as the reliability, maintainability, availability, etc., are all presented. The results show that the mixture model of three-parameter Weibull distribution, with advantages over other Weibull models, is suitable for modelling failure data of multiple NC machine tools with multiple failure modes and causes.

关键词： mixture model three-parameter Weibull distribution parameter estimation reliability analysis non-linear programming

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Adaptive firefly algorithm with chaos for mechanical design optimization problems

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APPLIED SOFT COMPUTING 2015年 36卷 152-164页

作者： Baykasoglu, Adil Ozsoydan, Fehmi Burcin Dokuz Eylul Univ Fac Engn Dept Ind Engn TR-35397 Izmir Turkey

Firefly algorithm (FA) is a newer member of bio-inspired meta-heuristics, which was originally proposed to find solutions to continuous optimization problems. Popularity of FA has increased recently due to its effectiveness in handling various optimization problems. To enhance the performance of the FA even further, an adaptive FA is proposed in this paper to solve mechanical design optimization problems, and the adaptivity is focused on the search mechanism and adaptive parameter settings. Moreover, chaotic maps are also embedded into AFA for performance improvement. It is shown through experimental tests that some of the best known results are improved by the proposed algorithm. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Firefly algorithm Chaotic maps Design optimization non-linear programming

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Improving the profitability of anaerobic digestion: is the public support framework compatible with participation in the day-ahead electricity market?

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RENEWABLE ENERGY 2019年第Aug.期139卷 560-572页

作者： Willeghems, Gwen Buysse, Jeroen EnergyVille ThorPk 8310 B-3600 Genk Belgium VITO Boeretang 200 B-2400 Mol Belgium Univ Ghent Fac Biosci Engn Dept Agr Econ Coupure Links 653 B-9000 Ghent Belgium

There is an increasing need for an alternative energy source within the electricity market to counterbalance the intermittent supply from renewable energy sources as their share in the market continues to grow. Anaerobic digestion could play a role in fulfilling this need through participation in the day-ahead electricity market. The potential for anaerobic digestion operators in Flanders, Belgium, and the impact of the current Flemish support policy framework on this potential are investigated by developing a non-linear optimization model that maximizes profits for the complete anaerobic digestion system, taking into account the current policy framework and a proposed alternative one. Our analysis indicates that there is a potential profit to be made for anaerobic digestion operators in the day-ahead market. However, the current framework of public support is not conducive to their participation. By allowing the same amount of support to be spread over a longer period of time, the use of flexible electricity production in the anaerobic digestion sector could be stimulated, and the profitability of this sector increased. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Biogas plant Gas storage Electricity market Flexible bioenergy non-linear programming Techno-economic analysis

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AC OPF for Smart Distribution Networks: An Efficient and Robust Quadratic Approach

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IEEE TRANSACTIONS ON SMART GRID 2018年第5期9卷 4613-4623页

作者： Franco, John F. Ochoa, Luis F. Romero, Ruben Univ Estadual Paulista UNESP BR-19274000 Rosana Brazil Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3010 Australia Univ Manchester Sch Elect & Elect Engn Manchester M13 9PL Lancs England Univ Estadual Paulista UNESP Fac Engn Ilha Solteira BR-15385000 Ilha Solteira Brazil

Smart grid schemes in which multiple network elements and participants are managed for the benefit of the distribution network (e.g., energy loss reduction, restoration, etc.) require sophisticated algorithms to control them in the most suitable manner while catering for network constraints. Such a complex decision making process can be solved by tailoring the ac optimal power flow (OPF) problem to the corresponding smart grid scheme. non-linear programming ac OPF formulations, however, can suffer from scalability and robustness issues which in turn might limit their adoption. Here, a novel quadratic programming formulation is proposed and compared against the non-linear, quadratically constrained, and linearized approaches. Two cases are carried out to assess their performance: 1) management of distributed generation units to maximize renewable energy harvesting (continuous control variables) and 2) control of capacitors to minimize energy losses (discrete control variables). The results demonstrate that the proposed quadratic approach significantly outperforms the more conventional formulations in both computational efficiency and robustness. This makes it a suitable alternative to be at the heart of the decision making of complex, real-time schemes to be adopted by future smart distribution networks.

关键词： Distribution networks non-linear programming optimal power flow quadratically constrained programming quadratic programming smart grids

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A stochastic AHP decision making methodology for imprecise preferences

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INFORMATION SCIENCES 2014年 270卷 192-203页

作者： Jalao, Eugene Rex Wu, Teresa Shunk, Dan Arizona State Univ Sch Comp Informat & Decis Syst Engn Tempe AZ 85281 USA Univ Philippines Dept Ind Engn & Operat Res Quezon City 1101 Philippines

Existing decision making methodologies like the Analytic Hierarchy Process (AHP) address imprecise pairwise comparisons by modeling crisp pairwise comparisons as fuzzy sets or a single type of probability distribution (e.g., uniform, triangular). However, one common issue faced by decision makers (DMs) is bounded rationality. That is, DMs have limited cognitive powers in specifying their preferences over multiple pairwise comparisons. This result to crisp as well as imprecise pairwise comparisons. Furthermore, given the ultimate goal of imprecise AHP is to make the decision, computing weights for the criteria and the alternatives from the imprecise preferences is a must. Hence, these various types of pairwise comparisons must be modeled using a single probability distribution for easy computation of the weights. In this research, a beta distribution is proposed to model the varying stochastic preferences of the DM. The method-of-moments methodology is used to fit the varying stochastic preferences of the DM into beta stochastic pairwise comparisons since it can represent a wide variety of probability distributions. Additionally, a non-linear programming model is then developed that calculates weights which maximize the preferences of the DM while maintaining a level of consistency. Comparison experiments are conducted using datasets collected from literature to validate the proposed methodology. Published by Elsevier Inc.

关键词： AHP Beta Distribution non-linear programming Imprecise Pairwise Comparisons Inconsistency

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