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Multi-degree cyclic flow shop robotic cell scheduling problem with multiple robots

INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2017年第8期30卷 805-821页

作者： Elmi, Atabak Topaloglu, Seyda Gaziantep Univ Dept Ind Engn Fac Engn Gaziantep Turkey Dokuz Eylul Univ Dept Ind Engn Fac Engn Izmir Turkey

This paper deals with the cyclic flow shop robotic cell scheduling problem with multiple robots, in which parts are processed successively on multiple machines with lower and upper bounds on processing times and the robots execute the transportation of parts between the machines. A novel mixed-integer linear programming model has been proposed for this problem. The proposed model simultaneously determines the optimal degree of the cyclic schedule and the optimal sequencing of the robots moves, which in return maximises the throughput rate. The validity of the proposed model is examined by a computational study on a set of randomly generated problem instances and solved using commercial optimisation software GAMS. The computational experiments indicate the efficiency of proposed model.

关键词： robotic cell cyclic scheduling multiple robots mixed-integer linear programming

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A lexicographic approach to the robust resource-constrained project scheduling problem

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2017年第1-2期24卷 143-157页

作者： Palacio, Juan D. Larrea, Olga L. Inst Tecnol Metropolitano Fac Ciencias Econ & Adm Dept Calidad & Prod Calle 7376A-354 Medellin Colombia

The resource-constrained project scheduling problem (RCPSP) is one of the most studied problems in the context of project scheduling. Given the NP-hardness nature of the problem, the RCPSP has been solved mainly using heuristics. Moreover, most of the studies consider a single objective for the problem. This paper presents an exact approach based on two mixed-integer linear programming (MILP) models to solve the RCPSP. The first MILP aims to minimize makespan, while the second MILP maximizes the robustness of the schedule. The mathematical formulations are solved using a lexicographic approach. We illustrate the effectiveness of the proposed models by solving standard instances for the RCPSP available in the project scheduling problems library (PSLIB) library. Computational results show that it is possible to find alternate optimal solutions with the maximum robustness subject to the minimum makespan for instances with up to 90 activities.

关键词： project scheduling resource constrained robust scheduling mixed-integer linear programming

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Supplier selection under failure risk, quantity and business volume discounts

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 104卷 145-155页

作者： Bohner, Christian Minner, Stefan Tech Univ Munich TUM Sch Management Arcisstr 21 D-80333 Munich Germany

We consider a supply chain problem with simultaneous supplier selection and order allocation for multiple products. The suppliers offer quantity and business volume discounts, and they are subject to failure. The buyer aims at minimizing total expected costs. We consider both all-units and incremental quantity discounts and find optimal solutions through mixed-integer linear programming. We discuss the trade-off between economies of scale and failure risk and show the cost reduction of our exact approach compared to a previously proposed heuristic. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Supplier selection Order allocation Quantity discount Business volume discount Failure risk mixed-integer linear programming

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A transportation network model with intelligent probabilistic travel times and two hybrid algorithms

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TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH 2017年第2期9卷 90-122页

作者： Shiripour, Saber Mahdavi-Amiri, Nezam Mahdavi, Iraj Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran Sharif Univ Technol Fac Math Sci Tehran Iran

A main component of a transportation network is travel time or distance. Due to stochastic events such as accidents and failures in roads, a deterministic estimation of the travel time between two cities or regions is impossible. Also, on special occasions like holidays, with increase in the traveling population in the transportation network, probabilities of occurrence of these events increase. The increase in traveling population has a direct effect on the estimation of travel times and subsequently on the decision-making process. Therefore, provision of an appropriate model for the intelligent probabilistic travel times to distribute the population in a transportation network is a practical necessity. Here, we study a capacitated location-multi allocation-routing problem with intelligent probabilistic travel times. In our study, the concept of intelligent probabilistic travel times incurs two issues: (1) consideration of some random factors in computing the travel times and (2) impact of the traveling population on these random factors simultaneously. Here, we consider three random factors of the time spent in traffic, the number of accidents and the number of road failures. It is assumed that server nodes and arcs have limited capacities for accepting the population. After proposing a function for computing the intelligent probabilistic travel time, we first formulate the problem as a mixed-integer nonlinear programming model, and then suitably transform it into a mixed-integer linear programming one. Our aim is to determine appropriate server locations among the candidate locations, allocate the existing population in each demand node to server locations, and find the movement path of each member to reach its corresponding server with respect to the simultaneous change of the probabilistic travel times so that the expected total transportation time is minimized. For small problems, the model is efficiently solvable by the CPLEX software package. For large probl

关键词： Intelligent probabilistic travel times multi allocation mixed-integer linear programming hybrid algorithms

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Optimal network design of hydrogen production by integrated utility and biogas supply networks

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APPLIED ENERGY 2017年第Dec.15期208卷 195-209页

作者： Hwangbo, Soonho Lee, Seungchul Yoo, Changkyoo Kyung Hee Univ Ctr Environm Studies Dept Environm Sci & Engn Yongin 446701 South Korea

This research aims to develop a mathematical model to construct a network model for producing hydrogen by integrated utility and biogas supply networks (IUBSNs). In this model, a utility supply network exists in a huge petrochemical industry while a biogas supply network consists of a wastewater treatment plant and anaerobic digestion. Pipelines connect the utility and biogas supply networks. The steam reforming process, which is the most well-known process able to generate large amounts of hydrogen, is employed to harness hydrogen as well as to integrate the two networks. In IUBSNs, the needed steam is obtained by optimizing a utility supply network while methane-rich biogas is generated by placing anaerobic digestion tanks into a number of wastewater treatment plants allocated by region. This study uses an algorithm for solving the mixed-integer linear programming problems to minimize the total annual costs of IUBSNs and simultaneously satisfy hydrogen demand. IUBSNs can be a great alternative to a hydrogen supply network that imports and consumes fossil fuels to produce hydrogen, furthermore, it is able to positively influence environmental issues through the reduction of the amount of fossil fuel used in petrochemical industries. A case study of the Republic of Korea illustrates the feasibility of the proposed model. Three cases (base case, only optimized utility supply networks, and IUBSNs) are conducted, and an increase in hydrogen demand is applied to each case. The results demonstrate that IUBSNs construction decreases the total costs by about 13% compared to the existing situation, and as hydrogen demand increases, the gas pipeline structure in IUBSNs employs a hub city to transport biogas flexibly.

关键词： Utility supply network Biogas supply network Hydrogen mixed-integer linear programming Optimization

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Non-discriminatory train dispatching in a rail transport market with multiple competing and collaborative train operating companies

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2017年第Jul.期80卷 148-174页

作者： Luan, Xiaojie Corman, Francesco Meng, Lingyun Delft Univ Technol Fac Mech Maritime & Mat Engn Dept Maritime & Transport Technol Sect Transport Engn & Logist Mekelweg 2 NL-2628 CD Delft Netherlands Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety 3 ShangYuanCun Beijing 100044 Peoples R China

Train dispatching is vital for the punctuality of train services, which is critical for a train operating company (TOC) to maintain its competitiveness. Due to the introduction of competition in the railway transport market, the issue of discrimination is attracting more and more attention. This paper focuses on delivering non-discriminatory train dispatching solutions while multiple TOCs are competing in a rail transport market, and investigating impacting factors of the inequity of train dispatching solutions. A mixed integer linear programming (MILP) model is first proposed, in which the inequity of competitors (i.e., trains and TOCs) is formalized by a set of constraints. In order to provide a more flexible framework, a model is further reformulated where the inequity of competitors is formalized as the maximum individual deviation of competitors' delay cost from average delay cost in the objective function. Complex infrastructure capacity constraints are considered and modelled through a big M-based approach. The proposed models are solved by a standard MILP solver. A set of comprehensive experiments is conducted on a real-world dataset adapted from the Dutch railway network to test the efficiency, effectiveness, and applicability of the proposed models, as well as determine the trade-off between train delays and delay equity. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Train dispatching Equity Train Operating Company (TOC) mixed-integer linear programming

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Parameter adaptation for generalized multiframe tasks: schedulability analysis, case study, and applications to self-suspending tasks

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REAL-TIME SYSTEMS 2017年第6期53卷 957-986页

作者： Peng, Bo Fisher, Nathan Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

The generalized multiframe task model (GMF) extends the sporadic task model and multiframe task model. Each frame in the GMF model contains an execution time, a relative deadline, and a minimum inter-arrival time. These parameters are fixed after task specification time in the GMF model. However, multimedia and adaptive control systems may be overloaded and no longer stabilized when the task parameters in such systems are not flexible. In order to address this problem, deadlines and periods of frames may change to alleviate temporal overload, e.g., in the parameter adaptation and elastic scheduling model. In this paper, we propose a new model GMF-PA (the GMF model with parameter adaptation). This model allows task parameters to be flexible in arbitrary-deadline systems. A necessary schedulability test based on mixed-integer linear programming is given to check the schedulability under EDF scheduling and optimally assign frame deadlines and periods at the same time. We also prove that the test is a sufficient and necessary schedulability test when frame deadlines and periods must be integers. An approximation algorithm is also deployed to reduce computational running time and indicates a sufficient schedulability test in general. The speed-up factor of our approximation algorithm is where can be arbitrarily small, with respect to the exact schedulability test of GMF-PA tasks under EDF. We also apply the GMF model to self-suspending tasks. By extending recent work on scheduling self-suspending tasks, we remove the assumption that frame deadlines are equally assigned in self-suspending tasks, and the system is extended from constrained-deadline systems to arbitrary-deadline systems. We have done extensive experiments to show that the schedulability ratio is improved using our techniques in our GMF-PA model.

关键词： Generalized multiframe task model Multiple-segment self-suspending tasks Uniprocessor scheduling mixed-integer linear programming Approximation algorithms

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Operational optimization of energy systems, 25 years – established and promising use cases

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Energy Procedia 2018年 149卷 15-24页

作者： Peter Stange Anja Matthees Thomas Sander TU Dresden Institute of Power Engineering Chair of Building Energy Systems and Heat Supply Helmholtzstraße 14 Dresden 01069 Germany

The operation of complex energy systems for the supply of heat and electricity leads to several questions regarding their optimal control, e.g. when to use which generator, when to load or unload energy storages or when to buy or sell energy. Usually it is a complex task to answer these questions with the aim of optimizing a specific objective and respecting all arising physical, technical and economic constraints. Since 25 years we are solving this problem for an energy provider of a medium-sized city with the aim of minimizing the operational costs. For this purpose, an own modelled mixed-integer linear optimization problem (MILP) has to be solved in association to the continuous operation of the energy system. The model includes but is not limited to several combined heat and power generators, heat accumulators, steam generators and auxiliary coolers. In this presentation we will give an outline about the wide range of given conditions that are successfully implemented for this application. Further we show our approach to generate realistic heat demand and power consumption forecasts which are both essential preconditions for obtaining reliable optimization results. In addition to the well – established MILP model in this specific use case we will outline some further promising applications of mathematical optimization in the context of energy systems. This includes the more precise modelling of energy storages, the computation of the optimal design of energy systems and the consideration of different or multiple targets in optimization. Moreover, we outline the problem of uncertain boundary conditions due to the growing amount of temporally hard to predict energy production and demand.

关键词： optimization of operation mixed-integer linear programming energy supply district heating demand forecast

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Performance comparison of energy supply systems under uncertain energy demands based on a mixed-integer linear model

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ENERGY 2017年 137卷 878-887页

作者： Yokoyama, Ryohei Nakamura, Ryo Wakui, Tetsuya Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan

In designing energy supply systems, several alternatives for design specifications are proposed, and their performances are evaluated and compared. In this paper, a method of comparing performances of two energy supply systems under uncertain energy demands is proposed based on a mixed-integer linear model. Uncertain energy demands are expressed by intervals. The minimum and maximum, and consequently their interval of the difference in the value of a performance criterion are evaluated for all the possible energy demands within their intervals. An optimization problem for this evaluation is formulated as a minimax mixed-integer linear programming one with integer and continuous operation variables. The problem is solved by evaluating upper and lower bounds for the optimal value of the difference in the value of the performance criterion repeatedly. In a case study, the minimum and maximum of the reduction in the annual total cost of a cogeneration system in comparison with a conventional energy supply system are evaluated, and the corresponding energy demands and operational strategies are identified. The influence of the uncertainty in energy demands on these results is also examined. Through the case study, the validity and effectiveness of the proposed method are clarified. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Energy supply Performance difference Uncertainty Minimax optimization mixed-integer linear programming

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A unified MILP model for topological structure of production well gathering pipeline network

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2017年 152卷 284-293页

作者： Zhang, Haoran Liang, Yongtu Zhang, Wan Wang, Bohong Yan, Xiaohan Liao, Qi China Univ Petr Beijing Key Lab Urban Oil & Gas Distribut Technol Beijing 102249 Peoples R China

Production well gathering pipeline network, usually characterized by various and complex structure and high investment, is one of significant parts of oil-gas field construction. Optimization of production well fluid gathering system is critical to reducing development cost. A variety of previous research focused on the issue. However, those methods were less applicable for dealing with the challenges of compatibility to various structures, integral optimization and finding the optimum. This paper focuses on stellated pipeline network, cascade dendritic pipeline network and insertion dendritic pipeline network, three common connection structures of gathering pipeline, and establishes a versatile mixed-integer linear programming model with considering terrain and obstacle conditions. Minimizing the total investment is the object of this model. Constraints of central processing facility, manifolds, flow rate, pipeline construction and connection mode are taken into consideration in the model. The optimal topological structure, position of central processing facility, diameter and route of each pipeline are obtained integrally by solving this model with GUROBI solver. Finally, two virtual oil-gas fields and a real-world gas field are taken as examples to verify the reliability and practicality of the model.

关键词： Oil-gas gathering pipeline network Topological structure Integral optimization mixed-integer linear programming

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