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International Conference on Industrial Design Engineering (ICIDE)

作者： Solid, Kent Komarudin Univ Indonesia Fac Engn Depok Indonesia

ISBN: (纸本)9781450348669

Indonesia is one of the countries with the largest mining resources in the world, and this sector contributes a lot to the country's economy. However, the negative impacts resulting from this sector are also not to be taken lightly, especially for the environment. One of the pollution produced is dust contamination. If not addressed, it will cause various health and safety disorders in the mine. For that, the use of water trucks became common in mining to water the streets. It takes careful planning on the activity of water trucks in the mines to maximize their effectiveness. Therefore, this study aims to build a route design and water truck scheduling using mixed integer Linier programming that effectively reduce dust pollution. The result of this research is a route and schedule arrangement for water truck that can be used to guide the activity of water truck in mining and penalty calculation for each scenario.

关键词： Coal & mineral mining inventory function mixed integer linear programming water truck optimization dust pollution Capacitated Arc Routing Problem

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mixed-integer linear programming Models for Coordinated Train Timetabling with Dynamic Demand

Mixed-Integer Linear Programming Models for Coordinated Trai...

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International Conference on Intelligent Transportation

作者： Jiateng Yin D’Ariano Andrea Yihui Wang Jing Xun Shuai Su Tao Tang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (纸本)9781538670255

In this paper, we study the optimization of coordinated train timetable in an urban rail network under the consideration of time-dependent passenger demands. This problem arises in large urban rail networks with multiple lines that the passengers may transfer among different lines to arrive at their destinations. We propose an exact formulation to generate the optimal train timetables of all the involved lines in a rail transit network synchronously, and our objective is to minimize the maximal level of crowdedness of stations. In particular, we introduce several sets of passenger flow variables that enable to model this complex problem as a mixed-integer linear programming (MILP) that is possible to be solved to the optimal solution. By considering the number of boarding and alighting passengers as passenger flow variables, we explicitly incorporates the number of in-vehicle passengers in the modelling framework to capture the train carrying capacity constraints. The formulated models first extend the passenger-oriented train timetabling models in existing literature from a single transit line to a whole connected network. Case studies are conducted to verify the effectiveness of the proposed model.

关键词： Rails mixed integer linear programming Rail transportation Optimization Safety Public transportation

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mixed integer linear programming Formulation for the Taxi Sharing Problem 1

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1st International Conference on Smart Cities (Smart-CT)

作者： Ben-Smida, Houssem E. Krichen, Saoussen Chicano, Francisco Alba, Enrique Univ Tunisia LARODEC Tunis Tunisia Univ Malaga Dept Lenguajes & Ciencias Computac Malaga Spain

ISBN: (数字)9783319395951

ISBN: (纸本)9783319395944;9783319395951

Given a group of people traveling from the same origin to multiple destinations, the Taxi Sharing Problem consists in assigning taxis to each person such that the total cost spent by the group of people is minimized. This problem arises in the context of Smart Mobility, where the resources of a city must be optimized to save costs and pollution while the mobility services are improved for the citizens. We propose a mixed integer linear programming formulation as an accurate way to solve the problem of taxi sharing. We empirically analyze our formulation solving different real-like instances of the problem with 9 to 69 people.

关键词： Taxi Sharing Problem mixed integer linear programming Smart Mobility Smart City

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A finite-time cutting plane algorithm for distributed mixed integer linear programming

A finite-time cutting plane algorithm for distributed mixed ...

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IEEE Annual Conference on Decision and Control

作者： Andrea Testa Alessandro Rucco Giuseppe Notarstefano Department of Engineering Università del Salento Lecce Italy

Many problems of interest for cyber-physical network systems can be formulated as mixed integer linear Programs in which the constraints are distributed among the agents. In this paper we propose a distributed algorithm to solve this class of optimization problems in a peer-to-peer network with no coordinator and with limited computation and communication capabilities. In the proposed algorithm, at each communication round, agents solve locally a small LP, generate suitable cutting planes, namely intersection cuts and cost-based cuts, and communicate a fixed number of active constraints, i.e., a candidate optimal basis. We prove that, if the cost is integer, the algorithm converges to the lexicographically minimal optimal solution in a finite number of communication rounds. Finally, through numerical computations, we analyze the algorithm convergence as a function of the network size.

关键词： Distributed algorithms Optimization Convergence Algorithm design and analysis mixed integer linear programming Routing

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Reduction of the two-step problem of stochastic optimal control with bilinear model to the problem of mixed integer linear programming

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AUTOMATION AND REMOTE CONTROL 2016年第12期77卷 2175-2192页

作者： Kibzun, A. I. Ignatov, A. N. Moscow State Aviat Inst Moscow Russia

Consideration was given to the two-step problem of stochastic optimization with a bilinear model which describes the problem of forming the securities portfolio consisting of some risk assets and one riskless asset. The probability of exceeding the given threshold of capital is used as the optimality criterion. At the second step, the piecewise constant control is used as the capital control. Determined were the upper and lower estimates of the probability functional. The problems of maximizing the upper and lower estimates of the probability functional were reduced to the problems of mixed integer linear programming by means of discretizing the probabilistic measure. An algorithm to seek an approximate solution to the original problem was proposed, and an example was considered.

关键词： original problem Capital stochastic optimal control bilinearity mixed integer linear programming reduction

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Generation of fiducial marker dictionaries using mixed integer linear programming

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PATTERN RECOGNITION 2016年 51卷 481-491页

作者： Garrido-Jurado, S. Munoz-Salinas, R. Madrid-Cuevas, F. J. Medina-Carnicer, R. Univ Cordoba Comp & Numer Anal Dept E-14071 Cordoba Spain

Square-based fiducial markers are one of the most popular approaches for camera pose estimation due to its fast detection and robustness. In order to maximize their error correction capabilities, it is required to use an inner binary codification with a large inter-marker distance. This paper proposes two mixed integer linear programming (MILP) approaches to generate configurable square-based fiducial marker dictionaries maximizing their inter-marker distance. The first approach guarantees the optimal solution, however, it can only be applied to relatively small dictionaries and number of bits since the computing times are too long for many situations. The second approach is an alternative formulation to obtain suboptimal dictionaries within restricted time, achieving results that still surpass significantly the current state of the art methods. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Fiducial markers MILP mixed integer linear programming Augmented reality Computer vision

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Dynamic optimal UAV trajectory planning in the National Airspace System via mixed integer linear programming

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2016年第9期230卷 1668-1682页

作者： Radmanesh, Mohammadreza Kumar, Manish Nemati, Alireza Sarim, Mohammad Univ Cincinnati Dept Mech & Mat Engn Cincinnati OH 45221 USA Univ Cincinnati Dept Elect Engn Cincinnati OH USA

Unmanned air vehicles (UAVs), which have been popular in military context, have recently attracted attention of many researchers because of their potential civilian applications. However, before the UAVs can be used for civilian applications, a systematic integration of UAVs in the National Airspace System (NAS) is needed that can allow safe operation of UAVs along with other manned aircrafts. One of the critical capabilities needed for safe operation of the UAVs in the NAS is the ability of UAV to carry out sense and avoid task which would allow the UAV to amend its path to avoid collision with other aircrafts. Despite recent technological advances, such as availability of automatic dependent surveillance broadcast that can transmit position of an aircraft to others in the vicinity, planning a collision-free path autonomously is still challenging in a dynamic environment. The objective of this paper is to develop a methodology for discovering a path for the UAV that meets mission goals, avoids collision, is optimal in terms of path length and, more importantly, is feasible. The paper formulates the problem of path planning using the mathematical paradigm of mixed integer linear programming and provides a solution strategy for solving this problem in the dynamic sense. The tasks of avoidance of obstacles and waypoint navigation are incorporated as constraints in the MILP problem. The paper presents the solution of the MILP problem and verifies the performance of the proposed methodology with regard to optimality of the solution and computational time requirement via several simulated scenarios of different complexities.

关键词： Unmanned air vehicles National Airspace Sysrem mixed integer linear programming automatic dependent surveillance broadcast trajectory planning

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Unit commitment for a compressor station by mixed integer linear programming

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JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING 2016年 30卷 338-342页

作者： Zuo, Lili Zhang, Xiaorui Wu, Changchun Yu, Yang China Univ Petr Beijing Key Lab Urban Oil & Gas Distribut Technol Natl Engn Lab Pipeline Safety 18 Fuxue Rd Beijing Peoples R China

When operating a compressor station, given its mass flow rate, inlet pressure and temperature, and discharge pressure, dispatchers need to decide which compressors to run and at what flow rates, i.e., the operating scheme of the station, to cut its energy costs. This paper addresses this problem under unsteady states. This means that at least one of the four given operating parameters is time-dependent, and therefore so is the operating scheme. The key constraints of the problem are the minimum uptime and downtime of each compressor, which interconnect the operating schemes at each time step and complicate the problem. The energy cost of a compressor unit is almost a linear function of its flow rate for a given inlet pressure, inlet temperature, and discharge pressure. Therefore, the optimization problem was formulated as a mixed integer linear programming (MILP) model, which was solved by CPLEX. The optimal operating schemes given by CPLEX were simulated to reevaluate the objective function, and the error of the linearized energy cost model was shown to be within 5%. The recalculated objective function values were 0.22%-1.18% higher than those of the true optimum. However, the MILP method was 0.49-64.95 times faster than the dynamic programming approach yielding global optimal solutions. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Compressor Unit commitment mixed integer linear programming CPLEX Dynamic programming

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mixed-integer linear programming Models for Teaching Assistant Assignment and Extensions

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SCIENTIFIC programming 2017年第1期2017卷 1-8页

作者： Qu, Xiaobo Yi, Wen Wang, Tingsong Wang, Shuaian Xiao, Lin Liu, Zhiyuan Univ Technol Sydney Sch Civil & Environm Engn Sydney NSW 2007 Australia Hong Kong Polytech Univ Dept Bldg & Real Estate Kowloon Hong Kong Peoples R China Wuhan Univ Sch Econ & Management Wuhan 430072 Peoples R China Hong Kong Polytech Univ Dept Logist & Maritime Studies Kowloon Hong Kong Peoples R China Natl Res Acad Sci Engn & Med Natl Res Council Washington DC 20001 USA Southeast Univ Sch Transportat Jiangsu Prov Collaborat Innovat Ctr Modern Urban Jiangsu Key Lab Urban ITS Nanjing Jiangsu Peoples R China

In this paper, we develop mixed-integer linear programming models for assigning the most appropriate teaching assistants to the tutorials in a department. The objective is to maximize the number of tutorials that are taught by the most suitable teaching assistants, accounting for the fact that different teaching assistants have different capabilities and each teaching assistant's teaching load cannot exceed a maximum value. Moreover, with optimization models, the teaching load allocation, a time-consuming process, does not need to be carried out in a manual manner. We have further presented a number of extensions that capture more practical considerations. Extensive numerical experiments show that the optimization models can be solved by an off-the-shelf solver and used by departments in universities.

关键词： mixed integer linear programming TEACHERS' assistants TUTORS & tutoring GRADUATE students UNDERGRADUATES

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Alternative mixed-integer linear programming Formulations for Shell and Tube Heat Exchanger Optimal Design

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 2017年第20期56卷 5970-5979页

作者： Goncalves, Caroline de O. Costa, Andre L. H. Bagajewicz, Miguel J. Rio de Janeiro State Univ UERJ Inst Chem Rua Sao Francisco Xavier 524 BR-20550900 Maracana RJ Brazil Univ Oklahoma Sch Chem Biol & Mat Engn Norman OK 73019 USA

In a recent article (Goncalves et al., AIChE J. 2017. DOI: 10.1002/aic.15556), we presented a mixed-integer linear programming formulation for the detailed design of shell and tube heat exchangers based on the Kern approach (Kern, D. Q Process Heat Transfer;McGraw Hill, 1950). The formulation relies on the use of standardized values for several mechanical parts, which we express in terms of discrete choices. Because we aim at having this model used as part of more complex models (i.e., heat exchanger networks synthesis), we identified a need to improve its computational efficiency. In this article, we explore several different modeling options to speed up solutions. These options are based on different alternatives of aggregation of the discrete values in relation to the set of binary variables. Numerical results show that these procedures allow large computational effort reductions.

关键词： mixed integer linear programming HEAT exchangers OPTIMAL designs (Statistics) HEAT transfer NUMERICAL analysis

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