Automated Switched Optical Networks(ASON) are based on control strategies that determine the optimal distribution of flows over different wavelengths,increase the profit,by allowing service providers to define and dep...
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Automated Switched Optical Networks(ASON) are based on control strategies that determine the optimal distribution of flows over different wavelengths,increase the profit,by allowing service providers to define and deploy new service *** this paper,we examine a demand elasticity based model for wavelength and flow assignment in multiwavelength optical *** model assumes that the physical and logical topology of the optical network,the maintenance cost for all physical links,and the traffic demands are known parameters.A mixedinteger optimization is employed to determine wavelength allocation and flow assignment of the requested traffic *** of the novelties of this work is the optimization cost function,used for the profit maximization of the transport service supplier.A case study is presented,showing how the bandwidth demand affects the supplier's ***,a comparison between the profitability of the proposed profit maximization and shortest path routing is provided.
Disassembly operations are required for most of manufactured products at the end of their life cycle. As economic activities and environmental pressures increase, the volume of product reverse flows are more and more ...
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ISBN:
(纸本)9781467383400
Disassembly operations are required for most of manufactured products at the end of their life cycle. As economic activities and environmental pressures increase, the volume of product reverse flows are more and more important and costly. In this context, we propose an optimization method to minimize cost in disassembly planning with lot sizing and lost sales. Comparing to others lot sizing problems with lost sales, this problem has some specificities that required original optimization methods. To this end, we proposed a metaheuristic based on genetic algorithm scheme that integrates some neighborhoods dedicated to this problem. The quality of the solutions is compared with those obtained from a mathematical programming solver for small instances and different configurations of the algorithm are compared. The metaheuristic allows finding good solutions in a reasonable computational time for this tactical problem for all instance sizes.
In Wireless Sensor Networks (WSNs) data transmission by using the highest available power level leads to energy wastage on certain links. Therefore, assigning the optimal transmission power for each link in a WSN is n...
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In Wireless Sensor Networks (WSNs) data transmission by using the highest available power level leads to energy wastage on certain links. Therefore, assigning the optimal transmission power for each link in a WSN is necessary to prolong the network lifetime. Transceivers of WSN nodes perform transmission power control by selecting one of the available discrete transmission power levels. As such, the power level set of a WSN transceiver is an important tool for achieving energy efficiency, yet, the power level sets are determined without considering their effects on WSN lifetime. In this study, we investigate the characteristics of the optimal transmission power level sets from WSN lifetime maximization perspective.
Face to critical contingence situations, the System Operator can require wind farms output reductions. The zonal Delegated Dispatches can act as interface between the System Operator and the producers, allowing a fast...
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Face to critical contingence situations, the System Operator can require wind farms output reductions. The zonal Delegated Dispatches can act as interface between the System Operator and the producers, allowing a faster and accurate answer. Three probable approaches are mathematically formulated and analyzed in the paper, separately considering the controllability and the possibility of disconnecting the wind farms. The methods are tested and compared by using a realistic test network, extracted from the Spanish national network.
This paper presents a new model to identify the topology status of power system. In the proposed model, measurement errors are unknown but belong to given bounded sets and the objective is to find a topology status wh...
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This paper presents a new model to identify the topology status of power system. In the proposed model, measurement errors are unknown but belong to given bounded sets and the objective is to find a topology status which is closest to the initial topology status and consistent with the sets of measurement uncertainties. Measurement equations are linearized by redefining state variables. mixedinteger nonlinear constraints are transformed to linear inequalities. Consequently, the problem is formulated as a mixedinteger quadratic constrained programming(MIQCP). Numerical tests on various systems show that the proposed formulation is accurate and computationally efficient.
Increasing social awareness together with the new regulations for carbon and waste management are forcing enterprises to reconsider their supply chains with respect to economic, social and environmental objectives. Fu...
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Increasing social awareness together with the new regulations for carbon and waste management are forcing enterprises to reconsider their supply chains with respect to economic, social and environmental objectives. Furthermore, cap and trade legislation for greenhouse gas emissions introduces a new level of complexity. This article presents a comprehensive methodology to address sustainable supply chain design problems where carbon emissions and total logistics costs, including suppliers and sub-contractors selection, technology acquisition and the choice of transportation modes, are considered in the design phase. The proposed methodology provides decision makers with a multi-objective mixed-integer linear programming model to determine the trade-off between economic and environmental considerations. This methodology is illustrated through the study of a Canadian firm operating in the steel industry which is facing a new legislation that caps carbon emissions. The results show how emission trading market can be used to reduce the carbon dioxide abatement cost.
Energy Storage Systems (ESS) could be widely available in power systems, in which case the short-term scheduling is one of the essential problems that need to be addressed. This paper presents a resources scheduling m...
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ISBN:
(纸本)9781467327299
Energy Storage Systems (ESS) could be widely available in power systems, in which case the short-term scheduling is one of the essential problems that need to be addressed. This paper presents a resources scheduling method for the optimal operation plan with the energy storage systems, which utilizes the mixed integer programming (MIP) based on the branch and bound method. The proposed method is evaluated on two case studies. One study examines a daily optimal operational plan for power supply resources and energy storage systems in an isolated micro-grid system. Another examines the optimal operational plan in a conventional power system with a large-scale energy storage system.
This paper describes how we solved 12 previously unsolved mixed-integerprogramming (MIP) instances from the MIPLIB benchmark sets. To achieve these results we used an enhanced version of ParaSCIP, setting a new recor...
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ISBN:
(纸本)9781509021413
This paper describes how we solved 12 previously unsolved mixed-integerprogramming (MIP) instances from the MIPLIB benchmark sets. To achieve these results we used an enhanced version of ParaSCIP, setting a new record for the largest scale MIP computation: up to 80,000 cores in parallel on the Titan supercomputer. In this paper we describe the basic parallelization mechanism of ParaSCIP, improvements of the dynamic load balancing and novel techniques to exploit the power of parallelization for MIP solving. We give a detailed overview of computing times and statistics for solving open MIPLIB instances.
For urban mass transit systems in the saturated passenger flow situation,the normal operation of trains might be disturbed by the unexpected disturbance.A large bunch of passengers might be stranded on platforms due t...
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For urban mass transit systems in the saturated passenger flow situation,the normal operation of trains might be disturbed by the unexpected disturbance.A large bunch of passengers might be stranded on platforms due to service gaps and the limited free capacity of *** this paper,we develop an automatic train regulation model which integrates two different regulation strategies and considers the pre-set automatic train operation(ATO) recommended speed *** specifically,a mixed integer programming(MIP) model is proposed which aims to jointly reduce the total train delay and the number of stranded *** consider a train holding strategy to futher balance the interval of two consecutive trains which can reduce the number of stranded passengers on the ***,a state-of-the-art mathematical solver CPLEX is adopted to solve the problem,which can obtain trade-off solutions in a reasonable ***,two experiments based on the operational data of the Beijing Subway Yizhuang Line are carried out to verify the effectiveness of the proposed approach.
Among generic technology management activities, rapid technology identification and selection stand as the significant determinants of technology adoption success in the digital transformation era. Especially for manu...
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Among generic technology management activities, rapid technology identification and selection stand as the significant determinants of technology adoption success in the digital transformation era. Especially for manufacturing SMEs in developing countries, rapid digital technologies are critical since they struggle to protect their competitiveness in global value chains threatened by digitalization. Previous studies introduce various multi-criteria decision-making model-based approaches to identify and select appropriate manufacturing technologies. However, these approaches were relatively rigid and required an advanced understanding of the technology for criteria and alternative settings and evaluation. Decision-makers need more flexible and scalable contextual frameworks for technology selection in digitalization. Since digital technologies offer both benefits and challenges, the decision-making models should reflect this dialectic nature of Industry 4.0 adoption and contextually optimize their decisions by combining multiple quantitative methods for technology identification and selection. Besides, case studies on digital technology selection are rare in manufacturing SMEs from developing country context in the literature. In this context, this study proposes a technology selection framework that utilizes the three dimensions (industry 4.0 technologies, benefits, and challenges) and combines AHP with a QFD-inspired intervention matrix and an optimization model by mixed integer programming (MIP). The proposed model is validated with a case study from the automotive supplier industry in Turkey with the data provided from interviews and a Delphi survey with 11 experts from the digitalization value chain of the selected industry. Case study results revealed that the highest benefits of industry 4.0 lie in process/quality efficiency improvement and reduced inventory. At the same time, data analytics and sensor technologies occurred as the most critical tools. Signific
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