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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Garroppo, Rosario G. Giordano, Stefano Nencioni, Gianfranco Scutella, Maria Grazia Univ Pisa Dip Ingn Informaz I-56100 Pisa Italy Univ Pisa Dipartimento Informat Pisa Italy

ISBN: (纸本)9781424492688

The paper describes and compares different approaches that can be used to design Network Power Management methods, with the aim of reducing the power consumption of telecommunication networks. The approaches are based on the solution of optimization problems that have, in general, a mixed integer nonlinear programming (MINLP) formulation. Given that the problems are NP-hard, exact methods for finding optimal solutions can be used only for scenarios of limited size. In this framework, the paper proposes a heuristic for finding a suboptimal solution of the Power Aware Routing and Network Design (PARND) problem, which is one of the more general design problems in Network Power Management. The simulation study highlights the capability of the proposed heuristic to obtain solutions near the optimum and to outperform the other approaches in terms of energy savings, while satisfying the constraints of the traffic demands.

关键词： Equations Green products NP-hard problems Network topology PARND problem Peer to peer computing Power demand Routing Switches heuristic approach integer programming mixed integer nonlinear programming network power management nonlinear programming optimization power aware routing and network design power consumption telecommunication network management telecommunication network routing

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Evacuation Problem Under the Nuclear Leakage Accident 40

Evacuation Problem Under the Nuclear Leakage Accident

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40th Chinese Control Conference (CCC)

作者： Yao, Canqi Chen, Shibo Yang, Zaiyue Harbin Inst Technol Sch Mechatron Engn Harbin 150000 Peoples R China Southern Univ Sci & Technol Shenzhen Key Lab Biomimet Robot & Intelligent Sys Dept Mech & Energy Engn Shenzhen 518055 Peoples R China Southern Univ Sci & Technol Guangdong Prov Key Lab Human Augmentat & Rehabil Shenzhen 518055 Peoples R China

ISBN: (纸本)9789881563804

To handle the detrimental effects brought by leakage of radioactive gases at nuclear power station, we propose a bus based evacuation optimization problem. The proposed model incorporates the following four constraints, 1) the maximum dose of radiation per evacuee, 2) the limitation of bus capacity, 3) the number of evacuees at demand node (bus pickup stop), 4) evacuees balance at demand and shelter nodes, which is formulated as a mixed integer nonlinear programming (MINLP) problem. Then, to eliminate the difficulties of choosing a proper M value in Big-M method, a Big-M free method is employed to linearize the nonlinear terms of the MINLP problem. Finally, the resultant mixed integer linear program (MILP) problem is solvable with efficient commercial solvers such as CPLEX or Gurobi, which guarantees the optimal evacuation plan obtained. To evaluate the effectiveness of proposed evacuation model, we test our model on two different scenarios (a random one and a practical scenario). For both scenarios, our model attains executable evacuation plan within given 3600 seconds computation time.

关键词： Nuclear leakage accident bus evacuation problem mixed integer nonlinear programming

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Optimal Allocation of FACTS Devises for Improving Volatage Stability with Two-Stage Brain Storm Optimization

Optimal Allocation of FACTS Devises for Improving Volatage S...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Takahashi, Tomoaki Mori, Hiroyuki Meiji Univ Dept Network Design Tokyo 1648525 Japan

ISBN: (纸本)9781728190488

In this paper, a new method is proposed for the optimal allocation of Flexible AC Transmission System (FACTS) devices for voltage stability. It aims at maximizing a margin between current power system conditions and the nose point of voltage stability with FACTS devices. The location and output variables of FACTS might be expressed as binary and conditions variables, respectively. Thus, the mathematical formulation results in one of mixed integer nonlinear programming problems. This paper proposes a new method that makes use of two-stage Brain Storm Optimization (TSBSO) as evolutional computation. The goal of optimization is to minimize a margin to the nose point of the PV /QV-curve of the continuation power flow calculation. As a practical optimization method, the idea of Robust Optimization is introduced into TSBSO to consider uncertainties in power systems. The effectiveness of the proposed method is demonstrated in the IEEE 30-node system.

关键词： FACTS Voltage stability Robust optimization Evolutionary computation Brain Storm Optimization mixed integer nonlinear programming

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Scheduling elective surgeries with sequence-dependent setup times to multiple operating rooms using constraint programming

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OPERATIONS RESEARCH FOR HEALTH CARE 2014年第3期3卷 160-167页

作者： Zhao, Zhaoxia Li, Xueping Univ Tennessee Dept Ind & Syst Engn 522 John D Tickle Bldg851 Neyland Dr Knoxville TN 37996 USA

The problem studied in this paper is to schedule elective surgeries (in contrast to urgent surgeries) to multiple operating rooms (ORs) in ambulatory surgical settings. We focus on three aspects of the daily scheduling decisions, including the number of ORs to open, the allocation of surgery-to-OR, and the sequence of surgeries in each OR. All the surgeries to be scheduled are known in advance, which is a common assumption for elective surgery scheduling problems. The surgeries belong to different types, and each OR can only allow certain types of surgeries to be performed. Before a surgery starts, some setup work needs to be done, such as sterilization and preparing required equipment. The setup times are assumed sequence-dependent, and both setup times and surgery durations are deterministic. The fixed costs of running the ORs are high;while sometimes overtime costs, which are even higher than the fixed costs, may occur when the surgeries cannot be done within the normal operating period of the ORs. We build a mixed integer nonlinear programming (MINLP) model and a Constraint programming (CP) model to solve this problem. The performance of these two models is tested on numerical examples, and the results show that the CP model is more efficient than the MINLP model in terms of the computational time and solution quality. We also examine the sensitivity of the solutions to the variation of surgery durations, and the analysis shows that the total costs do not change much when the variations of surgery durations are small. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Elective surgery scheduling Multiple operating rooms Sequence-dependent setup time Constraint programming mixed integer nonlinear programming

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Global transformer design optimization using deterministic and non-deterministic algorithms

Global transformer design optimization using deterministic a...

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20th International Conference on Electrical Machines (ICEM)

作者： Amoiralis, E. I. Tsili, M. A. Kladas, A. G. Univ Mil Educ Hellen Army Acad Sector Math & Engn Sci Dept Mil Sci Vari 16673 Greece Natl Tech Univ Athens Fac Elect & Comp Engn Athens GR-15780 Greece

ISBN: (纸本)9781467301428

The present paper compares the application of one deterministic and three non-deterministic optimization algorithms to global transformer design optimization. One deterministic optimization algorithm (mixed integer nonlinear programming), is compared to three non-deterministic approaches (Harmony Search, Differential Evolution and Genetic Algorithm). The comparison yields significant conclusions on the efficiency of the algorithms and the selection of the most suitable for the transformer design optimization problem.

关键词： transformers design optimization deterministic algorithms non-deterministic algorithms mixed integer nonlinear programming harmony search differential evolution genetic algorithm

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Maximizing the Lifetime of Delay-Sensitive Sensor Networks via Joint Routing and Sleep Scheduling

Maximizing the Lifetime of Delay-Sensitive Sensor Networks v...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Gu, Yunan Pan, Miao Li, Wei Texas So Univ Dept Comp Sci Houston TX 77004 USA

ISBN: (纸本)9781479923588

Network lifetime is critical to any battery operated wireless sensor networks (WSNs). Especially for delay-sensitive WSNs, it is challenging to prolong the network lifetime, while meeting the delay requirements of different applications. In this paper, we investigate how to optimize the network lifetime of delay-sensitive WSNs with respect to energy efficient routing and sleep scheduling. Instead of treating routing and sleep scheduling as two separate approaches, we have a joint consideration of them, and mathematically formulate the lifetime maximization problem under multiple constraints (i.e., routing, end-to-end delay bounds, sleep scheduling, energy consumption of transmission, receiving and listening, etc.). Since the formulated problem is a mixed integer non-linear programming (MINLP) problem and NP-hard to solve, we relax it into a linear programming (LP) problem and solve the relaxed problem for the upper bound. We also develop a heuristic algorithm for the feasible solution, which yields a lower bound of WSNs' lifetime. Through extensive simulations, we show that the solution found by the proposed algorithm is close to the optimal one and the proposed scheme is effective in prolonging the lifetime of delay-sensitive WSNs.

关键词： integer programming linear programming nonlinear programming telecommunication network routing telecommunication power management wireless sensor networks MINLP NP-hard problem WSN battery operated wireless sensor networks delay-sensitive wireless sensor networks energy efficient routing linear programming problem mixed integer nonlinear programming network lifetime maximization problem sleep scheduling Ad hoc networks Delays Routing Tin Upper bound Wireless communication Wireless sensor networks

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Optimal Energy Management of an Autonomous Hybrid Energy System 7

Optimal Energy Management of an Autonomous Hybrid Energy Sys...

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7th IEEE International Conference on Power and Energy (PECon)

作者： Obaro, Adewale Z. Munda, Josiah L. Siti, Mukwanga W. Tshwane Univ Technol Elect Engn Pretoria South Africa

ISBN: (纸本)9781538654316

The rising operating cost of power systems and over-utilization of fossil fuel deposits have led to continuous energy scarcity and a wide gap between energy demand and supply. These pose critical challenges across the world. The renewable energy sources (RESs) provide a viable and sustainable energy alternative which is capable of meeting the exponential energy growth, reducing over-dependency on fossil fuels as well as minimizing global warming. This paper presents an optimal control and management of an autonomous hybrid energy system (AHES) that reliably supplies energy demand at a minimum daily operating cost. The non-linear cost function is formulated as a mixed integer nonlinear programming (MINLP) problem to optimize the use of renewable resources and minimize the utilization of diesel generator (DG). The unpredictability inherent in RESs is addressed through the optimal design and management of multiple energy generation sources, and battery storage system (BSS). The MINLP optimization technique employed is validated with a dynamic commercial daily load profiles. The simulation results show that the proposed hybrid system significantly minimizes daily operating cost and improves supply reliability when compared to DG-single system.

关键词： hybrid energy system battery storage system mixed integer nonlinear programming energy management technique

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Solving Multi-objective Dynamic Travelling Salesman Problems by Relaxation 19

Solving Multi-objective Dynamic Travelling Salesman Problems...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Ricciardi, Lorenzo A. Vasile, Massimiliano Univ Strathclyde Glasgow Lanark Scotland

ISBN: (纸本)9781450367486

This paper describes a method to solve Multi-objective Dynamic Travelling Salesman Problems. The problems are formulated as multi-objective hybrid optimal control problems, where the choice of the target destination for each phase is an integer variable. The resulting problem has thus a combinatorial nature in addition to being a multi-objective optimal control problem. The overall solution approach is based on a combination of the Multi Agent Collaborative Search, a population based memetic multi-objective optimisation algorithm, and the Direct Finite Elements Transcription, a direct method for optimal control problems. A relaxation approach is employed to transform the mixed integer problem into a purely continuous problem, and a set of smooth constraints is added in order to ensure that the relaxed variables of the final solution assume an integer value. A special set of smooth constraints is introduced in order to treat the mutually exclusive choices of the targets for each phase. The method is tested on two problems: the first is a motorised Travelling salesman problem described in the literature, the second is a space application where a satellite has to de-orbit multiple debris. For the first problem, the approach is generating better solutions than those reported in the literature.

关键词： Multi-objective Optimisation Global Optimisation Optimal control mixed integer nonlinear programming Memetic Algorithms

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Branch and Bound algorithm for transmission network expansion planning using DC model

Branch and Bound algorithm for transmission network expansio...

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IEEE Lausanne Powertech

作者： Rider, Marcos J. Garcia, Ariovaldo V. Romero, Ruben Univ Estadual Campinas Dept Elect Energy Syst Campinas SP Brazil Univ Estadual Paulista Fac Engn Ilha Solteira Ilha Solteira SP Brazil

ISBN: (纸本)9781424421893

This paper presents an algorithm to solve the network transmission system expansion planning problem using the DC model which is a mixed non-lines integer programming problem. The major feature of this work is the use of a Branch-and-Bound (B&B) algorithm to directly solve mixed non-linear integer problems. Am efficient interior point method is used to solve the non-linear programming problem at each node of the B&B tree. Tests with several known systems are presented to illustrate the performance of the proposed method.

关键词： power transmission planning Branch-and-Bound algorithm higher order interior point method mixed integer nonlinear programming DC model

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Optimization of closed-loop Supply chain network design: a Water Cycle Algorithm approach 12

Optimization of closed-loop Supply chain network design: a W...

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12th International Conference on Industrial Engineering (ICIE)

作者： Khalilpourazari, Soheyl Mohammadi, Mohammad Kharazmi Univ Fac Engn Dept Ind Engn Tehran Iran

ISBN: (纸本)9781509004584

Supply chain network design is one of the most important problems that managers deal with in supply chain management (SCM). This paper presents a mathematical model for closed-loop supply chain network design. By solving the mathematical model facility locations, the flow of material and number of vehicles are determined such that the total supply chain costs are minimized. Due to complexity of the mathematical model of closed-loop supply chain, a novel Meta-heuristic algorithm named Water Cycle Algorithm is developed to solve the mathematical model of the problem. Various test problems are solved to evaluate the efficiency of the Water Cycle Algorithm.

关键词： Closed-loop supply chain Optimization Water Cycle Algorithm mixed integer nonlinear programming

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