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Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

ENERGIES 2014年第12期7卷 8554-8581页

作者： Stojiljkovic, Mirko M. Stojiljkovic, Mladen M. Blagojevic, Bratislav D. Univ Nis Fac Mech Engn Nis Nish 18000 Serbia

In this paper, a methodology for multi-objective optimization of trigeneration plants is presented. It is primarily applicable to the systems for buildings' energy supply characterized by high load variations on daily, weekly and annual bases, as well as the components applicable for flexible operation. The idea is that this approach should enable high accuracy and flexibility in mathematical modeling, while remaining efficient enough. The optimization problem is structurally decomposed into two new problems. The main problem of synthesis and design optimization is combinatorial and solved with different metaheuristic methods. For each examined combination of the synthesis and design variables, when calculating the values of the objective functions, the inner, mixed integer linear programming operation optimization problem is solved with the branch-and-cut method. The applicability of the exploited metaheuristic methods is demonstrated. This approach is compared with the alternative, superstructure-based approach. The potential for combining them is also examined. The methodology is applied for multi-objective optimization of a trigeneration plant that could be used for the energy supply of a real residential settlement in Nis, Serbia. Here, two objectives are considered: annual total costs and primary energy consumption. Results are obtained in the form of a Pareto chart using the epsilon-constraint method.

关键词： buildings energy supply combinatorial optimization metaheuristic methods mixed integer linear programming multi-objective optimization trigeneration

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Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2014年第19期52卷 5656-5674页

作者： Sueer, Guersel A. Ates, Ozan K. Mese, Emre M. Ohio Univ Russ Coll Engn & Technol Ind & Syst Engn Dept Athens OH 45701 USA

This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60-100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. The results of experimentation also showed that family splitting was observed in all multi-cell optimal solutions and therefore it can be concluded that family splitting is a good strategy for the problem considered in this paper.

关键词： cell scheduling group scheduling genetic algorithms mixed integer linear programming heuristics

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DESIGNING DISCRETE SEQUENTIAL TESTS VIA mixed integer programming

DESIGNING DISCRETE SEQUENTIAL TESTS VIA MIXED INTEGER PROGRA...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Michael Fauss Abdelhak M. Zoubir Signal Processing Group Technische Universitat Darmstadt Merckstrasse 25 64283 Darmstadt Germany

ISBN: (纸本)9781479928941

We show that the optimal design of non-randomized discrete sequential tests, i.e., tests whose test statistics take on only a countable number of states, can be modeled as a mixed integer linear problem. This is done by reformulating the difference equations describing the random walk on the integer lattice in terms of linear mixed integer constraints. We outline the general procedure and give a simple example to show how the proposed method can be used in practice.

关键词： programming Difference equation Random walk mixed integer Optimal design mixed integer linear programming Mixing

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Multi-product joint delivery planning in a retailers’ network under resource constraints

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International Journal of Systems Science: Operations and Logistics 2015年第3期2卷 125-134页

作者： Rahmouni, Mouna Hennet, Jean-Claude Fnaiech, Farhat Centre National de la Recherche Scientifique (CNRS) Aix Marseille University Marseille France Ecole Nationale Supérieure des Arts et métiers (ENSAM) Toulon University Marseille France Laboratory of Signal Image and Energy Mastery Higher School of Engineering of Tunis (ENSIT) University of Tunis Tunis Tunisia

The main objective of the JRP (joint replenishment problem) is to build a delivery programme so as to satisfy local demands while minimising the total cost including ordering and storage costs. The classical nonlinear formulation of this problem can be seen as a multi-product and multi-site extension of the economic order quantity (EOQ) problem. If demand rates are fixed and known, the problem allows a periodic solution, in which an optimal delivery programme repeats indefinitely. In the unconstrained case, the delivery plan has two levels of periodicity: a global periodicity for the delivery sequence and a particular periodicity for each product and site. The main purpose of this paper is to combine in the same model grouping, transportation, and storage issues. Constraints on transportation capacity and routing are introduced in a linear reformulation of the problem, leading to a better coordination of delivery schedules with respect to products and sites. The superiority of the proposed method is that it provides the optimal route of delivery for each tour and permits minimisation of the maximal delivery capacity, whereas other existing methods could not offer such important features. © 2015, © 2015 Taylor & Francis.

关键词： inventory theory joint replenishment problem Lagrangian relaxation mixed integer linear programming optimisation

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A network design model for biomass to energy supply chains with anaerobic digestion systems

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APPLIED ENERGY 2014年 130卷 289-304页

作者： Balaman, Sebnem Yilmaz Selim, Hasan Dokuz Eylul Univ Dept Ind Engn TR-35397 Izmir Turkey

Development and implementation of renewable energy systems, as a part of the solution to the worldwide increasing energy consumption, have been considered as emerging areas to offer an alternative to the traditional energy systems with limited fossil fuel resources and to challenge environmental problems caused by them. Biomass is one of the alternative energy resources and agricultural, animal and industrial organic wastes can be treated as biomass feedstock in biomass to energy conversion systems. This study aims to develop an effective supply chain network design model for the production of biogas through anaerobic digestion of biomass. In this regard, a mixed integer linear programming model is developed to determine the most appropriate locations for the biogas plants and biomass storages. Besides the strategic decisions such as determining the numbers, capacities and locations of biogas plants and biomass storages, the biomass supply and product distribution decisions can also be made by this model. Mainly, waste biomass is considered as feedstock to be digested in anaerobic digestion facilities. To explore the viability of the proposed model, computational experiments are performed on a real-world problem. Additionally, a sensitivity analysis is performed to account for the uncertainties in the input data to the decision problem. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Biomass to energy conversion systems Biofuel supply chain Anaerobic digestion systems Biogas mixed integer linear programming

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Improving the robustness in railway station areas

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2014年第1期235卷 276-286页

作者： Dewilde, Thijs Sels, Peter Cattrysse, Dirk Vansteenwegen, Pieter Univ Leuven KU Leuven Ctr Ind Management Traff & Infrastruct B-3001 Louvain Belgium Infrabel B-1070 Brussels Belgium Logically Yours BVBA B-2100 Deume Belgium

In order to improve the robustness of a railway system in station areas, this paper introduces an iterative approach to successively optimize the train routing through station areas and to enhance this solution by applying some changes to the timetable in a tabu search environment. We present our vision on robustness and describe how this vision can be used in practice. By introducing the spread of the trains in the objective function for, the route choice and timetabling module, we improve the robustness of a railway system. Using a discrete event simulation model, the performance of our algorithms is evaluated based on a case study for the Brussels' area. The computational results indicate an average improvement in robustness of 6.2% together with a decrease in delay propagation of about 25%. Furthermore, the effect of some measures like changing the train offer to further increase the robustness is evaluated and compared. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Transportation Robustness Railway timetabling Train routing Bottleneck scheduling mixed integer linear programming

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Multi-objectives, multi-period optimization of district energy systems: II-Daily thermal storage

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COMPUTERS & CHEMICAL ENGINEERING 2014年 71卷 648-662页

作者： Fazlollahi, Samira Becker, Gwenaelle Marechal, Francois Veolia Environm Rech & Innovat F-78520 Limay France Ecole Polytech Fed Lausanne Ind Energy Syst Lab CH-1015 Lausanne Switzerland

District heating is an efficient way of providing heat to urban areas. The use of storage tanks integrated with district heating network would permit to increase the annual utilization of base load equipment, avoiding over estimation of the size of backup equipment, and balancing the energy demand fluctuation during day and night. In the present work a multi-objective optimization model for sizing and operation optimization of district heating systems with heat storage tanks is presented. The model includes process design and energy integration techniques for optimizing the temperature intervals, the volume and the operation strategy of thermal storage tanks. The proposed model is demonstrated by means of two test cases. Results show that the efficiency, environmental impacts and total costs of an urban system can be improved after integrating the thermal storage by 4.7%, 5% and 2% respectively. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Daily thermal storage District energy systems mixed integer linear programming Evolutionary algorithm Multi-objective optimization CO2 mitigation

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An Optimal Energy Storage Control Strategy for Grid-connected Microgrids

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IEEE TRANSACTIONS ON SMART GRID 2014年第4期5卷 1785-1796页

作者： Malysz, Pawel Sirouspour, Shahin Emadi, Ali McMaster Univ McMaster Inst Automot Res & Technol MacAUTO Hamilton ON L8S 4K1 Canada McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada McMaster Univ Dept Mech Engn Hamilton ON L8S 4K1 Canada

This paper presents an online optimal energy/power control method for the operation of energy storage in grid-connected electricity microgrids. The approach is based on a mixed-integer-linear-program optimization formulated over a rolling horizon window, considering predicted future electricity usage and renewable energy generation. Performance objectives include electricity usage cost, battery operation costs, and utility oriented goals related to the peak demand and load smoothing. A robust counterpart formulation of the optimization problem is also proposed to handle uncertainty in energy demand/generation prediction in a computationally efficient way. Further reduction in the computations is achieved by employing variable time steps and relaxing binary constraints. A series of simulations demonstrate the effectiveness of various features of the proposed energy/power management methodology in different scenarios.

关键词： Adaptive control battery energy management microgrid mixed integer linear programming robust optimization rolling horizon smartgrid solar power wind power

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A Spatial multi-period long-term energy planning model: A case study of the Greek power system

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APPLIED ENERGY 2014年 115卷 456-482页

作者： Koltsaklis, Nikolaos E. Dagoumas, Athanasios S. Kopanos, Georgios M. Pistikopoulos, Efstratios N. Georgiadis, Michael C. Aristotle Univ Thessaloniki Dept Chem Engn Thessaloniki 54124 Greece Elect Market Operator SA Piraeus 18545 Greece Univ Piraeus Dept Int & European Studies Piraeus 18534 Greece Univ London Imperial Coll Sci Technol & Med Dept Chem Engn Ctr Proc Syst Engn London SW7 2AZ England

This paper presents a mixed-integer linear programming (MILP) model for the optimal long-term energy planning of a (national) power generation system. In order to capture more accurately the spatial and technical characteristics of the problem, the underlying geographical area (country) is divided into a number of individual networks that interact with each other. The proposed model determines the optimal planning of the power generation system, the selection of the power generation technologies, the type of fuels and the plant locations so as to meet the expected electricity demand, while satisfying environmental constraints in terms of CO2 emissions. Furthermore, the suggested model determines the electricity imports from neighbouring countries, the electricity transmission as well as the transportation of primary energy resources between domestic networks. A real case study concerning the Greek energy planning problem demonstrates the applicability of the proposed approach, which can provide policy makers with a systematic computer-aided tool to analyse various scenarios and technology options. Finally, a sensitivity analysis was conducted in order to capture the influence of some key parameters such as electricity demand, natural gas and CO2 emission price as well as wind power investment cost. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： mixed integer linear programming Energy systems engineering Generation expansion planning Power sector Carbon emissions

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Risk-Hedged Traffic Flow Management Under Airspace Capacity Uncertainties

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2014年第5期37卷 1487-1500页

作者： Sengupta, Prasenjit Tandale, Monish D. Menon, P. K. Optimal Synth Inc Los Altos CA 94022 USA

This paper presents a novel solution to the problem of air traffic flow management under airspace capacity uncertainty arising from weather or environmental effects. The traffic flow management problem is formulated as a stochastic linear program with multiple available routes between origin destination pairs, with the weather/environmental factors constraining the probable capacities along these routes. The performance index consists of the delays introduced by deterministic and stochastic capacity constraints. Primary impact of the weather/environmental factors is to require the rerouting of aircraft, causing additional delays. These additional delays require the aircraft to carry additional fuel or to incur costs associated with the failure to meet the schedules in hub-spoke operations. Thus, the variance of delays can be used to define the degree of risk in stochastic traffic flow management, and flow management algorithms that assure the variations in the delay below a specified value can be considered as providing a hedge against uncertain weather or environmental factors. The algorithm developed in this paper produces a risk-hedged decision that results in the least delay at a specified level of acceptable variance. This algorithm represents a dramatic departure from the more traditional stochastic traffic flow management algorithms, which minimize expected value of delays, without attempting to control their variances. The performance of the present stochastic traffic flow management algorithm is demonstrated on a use case representing National Airspace System operations on a regional scale.

关键词： Airspace Air Traffic Flow Management Air Route Traffic Control Center Dantzig Wolfe Decomposition Detroit Metropolitan Wayne County Airport Probability Distribution National Oceanic and Atmospheric Administration Graphics Processing Unit Coded Instrument Flight Procedures mixed integer linear programming

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