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1st International Conference on Intelligent Systems in Production Engineering and Maintenance (ISPEM)

作者： Kozlowski, Edward Mazurkiewicz, Dariusz Kowalska, Beata Kowalski, Dariusz Lublin Univ Technol Dept Quantitat Methods Management Fac Management Nadbystrzycka 38D PL-20618 Lublin Poland Lublin Univ Technol Dept Prod Engn Fac Mech Engn Nadbystrzycka 36 PL-20618 Lublin Poland Lublin Univ Technol Dept Water Supply & Wastewater Disposal Fac Environm Engn Nadbystrzycka 40B PL-20618 Lublin Poland

ISBN: (纸本)9783319644653;9783319644646

The cost of energy consumed in the course of pumping water from its sources constitutes a considerable share of the total operating costs borne by a water company. In order to optimize the operation of a water pumping station, it is essential to devise an appropriate pumps schedule. The aim of the work was to develop a smart tool which would facilitate decision-making by the operator of a water intake, including a group of wells, supplying actual municipal waterworks. The tool creates a real-time schedule for wells and pumps integrated with them, which constitutes a basis for a final decision made by the operator, related to the degree and period of their usage. The main criterion of facilitating the decision-making pertained to achieving the minimum energy consumption during pumping water from a well to a reservoir tank, while simultaneously keeping all the wells on full stand-by. The schedule was prepared by means of binary linear programming. In this method, both the function of the goal and the limiting functions are linear, whereas the particular variables belong to the set {0,1}.

关键词： Water pumping station Pump schedule binary linear programming

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An algorithm for generalized fuzzy binary linear programming problems

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2001年第3期133卷 496-511页

作者： Yu, CS Li, HL Shih Chien Univ Dept Informat Management Taipei 10497 Taiwan Natl Chiao Tung Univ Inst Informat Management Hsinchu 30050 Taiwan

Fuzzy binary linear programming (FBLP) problems are very essential in many fields such as assignment and assembly line balancing problems in operational research, multiple projects, locations, and candidates selection cases in management science, as well as representing and reasoning with prepositional knowledge in artificial intelligence. Although FBLP problems play a significant role in human decision environment, not very much research has focused on FBLP problems. This work first proposes a simple means of expressing a triangular fuzzy number as a linear function with an absolute term. A method of linearizing absolute terms is also presented. The developed goal programming (GP) model weighted by decision-makers' (DMs) preference aims to optimize the expected objective function and minimize the sum of possible membership functions' deviations. After presented a novel way of linearizing product terms, the solution algorithm is proposed to generate a crisp trade-off promising solution that is also an optimal solution in a certain sense. Three examples, equipment purchasing choice, investment project selection, and assigning clients to project leaders, illustrate that the proposed algorithm can effectively solve generalized FBLP problems. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： fuzzy mathematical programming binary linear programming

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Global optimum economic designing of grid-connected photovoltaic systems with multiple inverters using binary linear programming

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SOLAR ENERGY 2019年第May期183卷 842-850页

作者： Bakhshi-Jafarabadi, Reza Sadeh, Javad Soheili, Adel Ferdowsi Univ Mashhad Elect Engn Dept Fac Engn Mashhad Razavi Khorasan Iran

Nowadays, grid-connected photovoltaic (GCPV) system is known as a top leading technology among all resources. However, it still suffers from drastic investment costs. Detailed economic studies should be conducted in this regard to make this technology as gainful as possible. A practical approach is the "optimum economic design", trying to find an electrically possible layout, i.e. number of series modules and parallel strings as well as the inverter number with the highest profit. This problem is inherently an quadratic integer programming owing to the multiplication of two integer variables in its objective function and some technical constraints. This nonlinear problem should be solved by exhaustive search methods, including comparative and evolutionary algorithms (EAs) such as particle swarm optimization (PSO) and genetic algorithm (GA). In this paper, a new formulation based on the definition of new binary variables has been proposed to convert this problem to the binary linear programming (BLP). The provided method finds the global optimum solution in a scale of seconds while EAs have to be run numerous times in a scale of hours to reach a sufficiently good answer. Moreover, although current methodologies are rarely covered GCPV systems with multiple inverter types, this formulation can be easily developed for systems with several inverter types. The simulations of a 1.1 MW power plant system endorse that the output design provided by the proposed method assures 95,000 $ (1.94%) higher profit compared with those presented by GA. The sensitivity analysis, provided for the prototype system by the efficient new algorithm, also unveils it is economically viable for even 52% of the current feed-in tariff, 40% energy generation lower than the estimated value and 1.1 $/W price rise for the initial investment.

关键词： Grid-connected photovoltaic system Optimum economic design Quadratic integer programming binary linear programming Global optimum solution

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Coupled binary linear programming-Differential Evolution Algorithm Approach for Water Distribution System Optimization

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2014年第5期140卷 585-597页

作者： Zheng, Feifei Simpson, Angus R. Zecchin, Aaron C. Univ Adelaide Sch Civil Environm & Min Engn Adelaide SA 5005 Australia

A coupled binary linear programming-differential evolution (BLP-DE) approach is proposed in this paper to optimize the design of water distribution systems (WDS). Three stages are involved in the proposed BLP-DE optimization method. In the first stage, the WDS that is being optimized is decomposed into trees and the core using a graph algorithm. binary linear programming is then used to optimize the design of the trees during the second stage. In the third stage, a differential evolution (DE) algorithm is utilized to deal with the core design while incorporating the optimal solutions for the trees obtained in the second stage, thereby yielding near-optimal solutions for the original whole WDS. The proposed method takes advantage of both the BLP and DE algorithms: BLP is capable of providing a global optimal solution for the trees (no loops involved) with great efficiency, and a DE is able to efficiently generate good quality solutions for the core (loops involved) with a reduced search space compared to the original full network. Two benchmark WDS case studies and one real-world case study (with multiple demand loading cases) with a number of decision variables ranging from 21-96 are used to verify the effectiveness of the proposed BLP-DE optimization approach. Results show that the proposed BLP-DE algorithm significantly outperforms other optimization algorithms in terms of both solution quality and efficiency.

关键词： Differential evolution Optimization Water distribution systems binary linear programming

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A binary linear programming-Based K-Means Algorithm For Clustering with Must-Link and Cannot-Link Constraints

A Binary Linear Programming-Based K-Means Algorithm For Clus...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Baumann, Philipp Univ Bern Dept Business Adm Schuetzenmattstr 14 CH-3012 Bern Switzerland

ISBN: (纸本)9781538672204

Clustering is probably the most extensively studied problem in unsupervised learning. Traditional clustering algorithms assign objects to clusters exclusively based on features of the objects. Constrained clustering is a generalization of traditional clustering where additional information about a dataset is given in the form of constraints. It has been shown that the clustering accuracy can be improved substantially by accounting for these constraints. We consider the constrained clustering problem where additional information is given in the form of must-link and cannot-link constraints for some pairs of objects. Various algorithms have been developed for this specific clustering problem. We propose a binary linear programming-based k-means approach that can consider must-link and cannot-link constraints. In a computational experiment, we compare the proposed algorithm to the DILSCC algorithm, which represents the state-of-the-art. Our results on 75 problem instances indicate that the proposed algorithm delivers better clusterings than the DILSCC algorithm in much shorter running time.

关键词： Constrained clustering must-link cannot-link k-means binary linear programming

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A HYBRID HEURISTIC BASED ON SELF-ORGANISING MAPS AND binary linear programming TECHNIQUES FOR THE CAPACITATED P-MEDIAN PROBLEM 33

A HYBRID HEURISTIC BASED ON SELF-ORGANISING MAPS AND BINARY ...

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33rd International European Council for Modelling and Simulation Conference on Modelling and Simulation, ECMS 2019

作者： Steglich, Mike Univ Appl Sci Wildau Hsch Ring 1 D-15745 Wildau Germany

ISBN: (纸本)9783937436654

This paper proposes a new hybrid heuristic (SomAla) for the capacitated p-median problem (CPMP) which combines a self-organising map (SOM), integer linear programming, an alternating location-allocation algorithm (ALA) and a partial neighbourhood optimisation. To improve the performance of the algorithm, the structure of the CPMP is exploited for several size-reduction methods and also for variable-fixing techniques. The capability of this algorithm to find good solutions in reasonable times for large problem instances has been tested on several benchmark instances.

关键词： capacitated p-median problem heuristic self-organising maps alternating location-allocation algorithm binary linear programming partial neighbourhood optimisation

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A binary linear programming-Based K-Means Approach for the Capacitated Centered Clustering Problem

A Binary Linear Programming-Based K-Means Approach for the C...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Baumann, Philipp Univ Bern Dept Business Adm Schuetzenmattstr 14 CH-3012 Bern Switzerland

ISBN: (纸本)9781728138046

The k-means algorithm is one of the most popular clustering algorithms in the machine learning community. Its simplicity and scalability make it the primary choice for many clustering applications. We introduce here a variant of the k-means algorithm that can account for complex side constraints. The key idea is to use binary linear programming for assigning objects to clusters. Unlike existing extensions of the k-means algorithm that are designed for accommodating specific types of constraints, our approach can be applied to a wide range of constrained clustering problems with minor modifications. We demonstrate the effectiveness and efficiency of the proposed approach by comparing it to a state-of-the-art algorithm on a test set that comprises 18 instances of the capacitated centered clustering problem. The proposed approach performed particularly well on large-sized instances with more than 100 clusters. It even found new best-known solutions for the four largest instances in the test set.

关键词： Capacitated centered clustering k-means binary linear programming

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V2G Electric Vehicle Charging Scheduling for Railway Station Parking Lots Based on binary linear programming

V2G Electric Vehicle Charging Scheduling for Railway Station...

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IEEE International Energy Conference (ENERGYCON)

作者： Sarabi, Siyamak Davigny, Arnaud Riffonneau, Yann Robyns, Benoit Univ Lille Cent Lille Arts & Metiers Paris Tech HEIEA 2697L2EP F-59000 Lille France ADEME 20 Ave GresilleBP 90406 F-49004 Angers France SNCF Innovat & Res 40 Ave Terroirs de France F-75611 Paris France

ISBN: (纸本)9781467384636

This paper proposes a V2G charging scheduling scheme for energy invoice minimization of railway station parking lots hosting plug-in electric vehicles. Using a two layer optimization technique the daily load profile of the railway station is reduced in order to increase the load factor and minimizing the annual energy invoice (AEI) of the station. binary linear programming is used as second layer for charging/discharging scheduling problem. The final results shows interests of using the proposed approach conducting its impact on minimizing annual optimum subscribed power, maximum demand power and annual energy invoice.

关键词： Plug-in electric vehicle vehicle-to-grid binary linear programming railway stations

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Optimizing Customer Assignments to Direct Marketing Activities: A binary linear programming Formulation

Optimizing Customer Assignments to Direct Marketing Activiti...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Bigler, T. Baumann, P. Kammermann, M. Univ Bern Dept Business Adm Schuetzenmattstr 14 CH-3012 Bern Switzerland

ISBN: (纸本)9781728138046

Direct marketing has become a fundamental advertising method in many industries. In direct marketing, companies target specific customers with personalized product offers. By optimally assigning customers to direct marketing activities, the effectiveness of direct marketing campaigns can be greatly increased. In this paper, we study a real-world customer assignment problem of a leading telecommunications provider in Switzerland. The planning problem contains many business and customer-specific constraints that have not yet been covered in the literature. We propose a binary linear programming formulation that solves instances involving up to one million customers and over 100 direct marketing activities to optimality in short running time. The novel formulation delivers substantially better solutions in terms of expected profit than the current practice at the company.

关键词： Direct marketing customer assignment real-world problem binary linear programming

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Novel binary linear programming for High Performance Clock Mesh Synthesis

Novel Binary Linear Programming for High Performance Clock M...

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IEEE and ACM International Conference on Computer-Aided Design

作者： Cho, Minsik Pan, David Z. Puri, Ruchir IBM Corp Thomas J Watson Res Ctr Yorktown Hts NY 10598 USA Univ Texas Austin Dept ECE Austin TX 78712 USA

ISBN: (纸本)9781424481927

Clock mesh is popular in high performance VLSI design because it is more robust against variations than clock tree at a cost of higher power consumption. In this paper, we propose novel techniques based on binary linear programming for clock mesh synthesis for the first time in the literature. The proposed approach can explore both regular and irregular mesh configurations, adapting to non-uniform load capacitance distribution. Our synthesis consists of two steps: mesh construction to minimize total capacitance and skew, and balanced sink assignment to improve slew/skew characteristics. We first show that mesh construction can be analytically formulated as binary polynomial programming (a class of nonlinear discrete optimization), then apply a compact linearization technique to transform into binary linear programming, significantly reducing computational overhead. Second, our balanced sink assignment enables a sink to tap the least loaded mesh segment (not the nearest one) with another binary linear programming which reduces both slew and skew. Experiments show that our techniques improve the worst skew and total capacitance by 14% and 15% over the state-of-the-art clock mesh algorithm [19] on ISPD09 benchmarks.

关键词： VLSI balanced sink assignment binary linear programming binary polynomial programming clocks compact linearization technique high performance VLSI design high performance clock mesh synthesis linear programming linearisation techniques mesh construction mesh generation nonlinear discrete optimization polynomial approximation

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