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Multi-objective optimization for the multi-mode finance-based project scheduling problem

Frontiers of Engineering Management 2020年第2期7卷 223-237页

作者： Sameh Al-SHIHABI Mohammad AlDURGA Industrial Engineering Department University of JordanAmman 11942Jordan Systems Engineering Department King Fahd University of Petroleum&MineralsDhahran 31261Kingdom of Saudi Arabia

The finance-based scheduling problem(FBSP)is about scheduling project activities without exceeding a credit line financing *** FBSP is extended to consider different execution modes that result in the multi-mode FBSP(MMFBSP).Unfortunately,researchers have abandoned the development of exact models to solve the FBSP and its ***,researchers have heavily relied on the use of heuristics and meta-heuristics,which do not guarantee solution *** exact models are available for contractors who look for optimal solutions to the multi-objective ***,which is an exact solver,has witnessed a significant decrease in its computation ***,its current version,CPLEX 12.9,solves multi-objective optimization *** study presents a mixed-integer linear programming model for the multi-objective *** CPLEX 12.9,we discuss several techniques that researchers can use to optimize a multi-objective *** test our model by solving several problems from the *** also show how to solve multi-objective optimization problems by using CPLEX 12.9 and how computation time increases as problem size *** small increase in computation time compared with possible cost savings make exact models a must for ***,the linear programming-relaxation of the model,which takes seconds,can provide an excellent lower bound.

关键词： multi-objective optimization finance-based scheduling multi-mode project scheduling mixed-integer linear programming CPLEX

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Integrated Demand Response programs and energy hubs retail energy market modelling

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ENERGY 2021年 234卷 121239-121239页

作者： Aghamohammadloo, Hossein Talaeizadeh, Valiollah Shahanaghi, Kamran Aghaei, Jamshid Shayanfar, Heidarali Shafie-khah, Miadreza Catalao, Joao P. S. Iran Univ Sci & Technol Ctr Excellence Power Syst Automat & Operat Sch Elect Engn Tehran Iran Iran Univ Sci & Technol Sch Elect Engn Tehran Iran Iran Univ Sci & Technol Fac Ind Engn Tehran Iran Lappeenranta Lahti Univ Technol LUT Sch Energy Syst Lappeenranta Finland Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal

The present research aims to formulate competition in a retail energy market in the presence of an Integrated Demand Response (IDR) program to reduce prosumer costs and increase retailer profits. This gives prosumers more degrees of freedom to reduce their energy costs. The retail energy market includes retailers and prosumers equipped with an energy hub containing a boiler for producing heat and combined heat and power (CHP). Retailers aim to maximize profit, whereas prosumers seek to minimize their costs. Hence, a multi-leader-follower game with a bi-level program emerges in which the upper level deals with the profit maximization of each retailer while the lower level considers the cost minimization of each prosumer. The strategic behaviour of each retailer is modelled as a Mathematical Program with Equilibrium Constraints (MPEC) problem. Simultaneously solving all MPECs, which leads to an Equilibrium Problem with Equilibrium Constraints (EPEC), determines the market equilibrium point. The equilibrium point is achieved using mathematical, analytical methods and linearization of nonlinear constraints by accurate techniques. Two different case studies are developed to investigate how the number of retailers influences the market equilibrium point. The first case includes two retailers, while the second case considers an increase in the number of retailers. The results demonstrate that with an increase in retailers' number, their competition increases, causing the prosumers costs to reduce. Furthermore, our results suggest the IDR impact on reduced prosumers cost and increased retailers profit. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Retail energy market Demand response mixed-integer linear programming Energy hub Combined heat and power

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A kernel search heuristic for a fair facility location problem

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COMPUTERS & OPERATIONS RESEARCH 2021年 132卷 105292-105292页

作者： Filippi, C. Guastaroba, G. Huerta-Munoz, D. L. Speranza, M. G. Univ Brescia Dept Econ & Management Cda S Chiara 50 Brescia Italy Univ Autonoma Nuevo Leon Grad Program Syst Engn San Nicolas De Los Garza 66455 NL Mexico

We consider an uncapacitated location problem where p facilities have to be located in order to serve a given set of customers, and we assume that a customer requesting for a service has to reach a facility at his/her own cost. In this setting, a central issue is that of fairness among customers for the accessibility to the services provided. Every choice regarding the location of facilities corresponds to a distance distribution of customers to reach an open facility. Minimizing the average of this distribution would lead to a p-median problem, where system efficiency is optimized but the fair treatment of users is neglected. Minimizing the maximum (worst-case) of the distribution would lead to a p-center problem, where the unfair treatment of users is mitigated but system efficiency is neglected. To compromise between these two extremes, we minimize the conditional beta-mean, i.e., the average distance traveled by the 100 x beta% of customers farther from a facility. We call Fair Facility Location Problem (FFLP(beta)) the resulting optimization problem, which is formulated as a mixed-integer linear Program (MIP) with a proven integer-friendly property. We propose a heuristic framework to produce a set of representative solutions to the FFLP(beta). The framework is based on Kernel Search, a heuristic scheme that has been shown to obtain high-quality solutions for a number of MIPs. Computational experiments are reported to validate the quality of the solutions found by the proposed solution algorithm, and to provide some general guidelines regarding the trade-off between average and worst-case optimization. Finally, we report on a case study stemming from the screening activities related to the pandemic triggered by the SARS-CoV-2 virus. The case study regards the optimal location of a number of drive-thru temporary testing sites for collecting swab specimens.

关键词： Location problems Fairness Kernel search mixed-integer linear programming

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Optimal electrification of off-grid smart homes considering flexible demand and vehicle-to-home capabilities

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APPLIED ENERGY 2021年 298卷 117184-117184页

作者： Tostado-Veliz, Marcos Leon-Japa, Rogelio S. Jurado, Francisco Univ Jaen Dept Elect Engn Jaen 23700 Spain

The emergence of novel demand-side management strategies is provoking that residential consumers cannot be longer categorized as inflexible loads. In that sense, new paradigms such as flexible demand and vehicle-to-home capabilities have appeared on pursuing a more efficient management of the different domestic assets such as smart appliances, small renewable generators and storage facilities. Consideration of such kind of management strategies plays a vital role on designing stages of electrifications systems for isolated homes. In this regard, a proper evaluation of possible demand-side capabilities enables a more accurate evaluation of the electrification project. This paper tackles this issue by developing a mixed integer linear programming formulation for optimal planning of electrification systems for off-grid dwellings. The developed framework allows to incorporate and analyse advanced demand-side strategies such as deferrable loads and vehicle-to-home processes by evaluating different project costs over various time horizons. The proposed approach is applied to a benchmark off-grid residential case study and various results are provided and analysed. As the most relevant result, it is worth remarking that total project cost can be reduced by -21.2% and -25.73% by considering flexible demand and vehicle-to-home capabilities, respectively. Nevertheless, the highest monetary savings were achieved when both strategies are jointly adopted, reducing the total project cost up to -41.5%. The reported results demonstrate the importance of considering the different demand-side strategies on planning stages of electrification systems for off-grid dwellings.

关键词： Off-grid smart home Flexible demand Vehicle-to-home mixed-integer linear programming

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Electricity distribution system planning considering incentive reliability regulations

Electricity distribution system planning considering incenti...

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作者： Jooshaki, Mohammad Aalto University

学位级别：博士

Electricity distribution systems are dynamically expanded in anticipation of new demands. Cost and reliability are the most important factors in finding the optimal plans for the network expansion. Recently, implementation of incentive reliability regulations has accentuated the role of reliability considerations in distribution systems studies. This is because such incentive schemes create a direct link between distribution companies’ revenues and their service reliability. Thus, these schemes have changed the role of reliability from a technical constraint to an economic factor. In this occasion, distribution companies require new techniques to incorporate the effects of incentive reliability regulations in their planning studies to get the most benefits. Motivated by these points, in this dissertation, various mathematical models are developed to incorporate the incentive reliability regulations into the planning studies of electricity distribution networks. Due to the rapid pace of technological advances in distribution systems, the proposed models consider a wide range of possible scenarios for future networks such as energy hubs, preventive maintenance scheduling, interconnection with natural gas distribution networks, and integration of various distributed generation technologies. In this respect, mathematical models for co-expansion planning of integrated electricity and natural gas networks, optimal scheduling of preventive maintenance actions, and optimal energy hub planning are devised. In addition, various frameworks are proposed to investigate the impacts of parameters of the incentive reliability schemes on distribution companies performance and potential outcomes of the implementation of the incentive regulations. In order to incorporate the reliability regulations into the panning studies, reliability indices must be quantified. Nonetheless, conventional reliability assessment techniques are not applicable due to their limitations. Novel reliabili

关键词： distributed generation electricity power distribution system electricity distribution system planning energy hub expansion co-planning expansion planning incentive reliability regulations mixed-integer linear programming

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Optimizing Charging Infrastructures of Electric Bus Routes to Minimize Total Ownership Cost

Optimizing Charging Infrastructures of Electric Bus Routes t...

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20th IEEE International Conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power Systems Europe Conference (I and CPS Europe)

作者： Lotfi, Mohamed Pereira, Pedro Paterakis, Nikolaos Gabbar, Hossam A. Catalao, Joao P. S. Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal Ontario Tech Univ Fac Energy Syst & Nucl Sci Oshawa ON L1G 8C4 Canada Eindhoven Univ Technol TU E Dept Elect Engn NL-5600 MB Eindhoven Netherlands Ontario Tech Univ Fac Engn & Appl Sci Oshawa ON L1G 8C4 Canada

ISBN: (纸本)9781728174556

Electrification of public transport systems has become a strategic priority due to the highly versatile potential of electric vehicles (EVs) as distributed energy resources (DERs) Despite the logistic ease of transitioning conventional public transport systems to fully-electric ones, the latter must be properly designed to adhere to technical constraints and minimize their total ownership cost (TOC). Most published work addresses this issue with a narrow scope, such as modeling a very specific case study, leading to non-generic models which are difficult to apply for a universal case. In this study, a mixed-integer linear programming (MILP) model is formulated to model a generic public transport network, comprising the routes, electric bus models, and charging infrastructures. The objective function minimizes the TOC of a generic network, which can be applied to any universal case study. The constructed model is tested by simulating a system with different routes, bus models, and types of chargers to obtain the optimal configuration of the charging infrastructure.

关键词： Battery Sizing Electric buses mixed-integer linear programming Optimal Charging Infrastructure

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Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks 10

Two Reformulation Approaches to Maximum-A-Posteriori Inferen...

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10th International Conference on Probabilistic Graphical Models (PGM)

作者： Maua, Denis Deratani Ribeiro, Heitor Reis Katague, Gustavo Perez Antonucci, Alessandro Univ Sao Paulo Inst Math & Stat Sao Paulo Brazil Ist Dalle Molle Studi Intelligenza Artificiale Lugano Switzerland

Sum-product networks are expressive efficient probabilistic graphical models that allow for tractable marginal inference. Many tasks however require the computation of maximum-a-posteriori configurations, an NP-hard problem for such models. To date there have been very few proposals for computing maximum-a-posteriori configurations in sum-product networks. This is in sharp difference with other probabilistic frameworks such as Bayesian networks and random Markov fields, where the problem is also NP-hard. In this work we propose two approaches to reformulate maximuma-posteriori inference as other combinatorial optimization problems with widely available solvers. The first approach casts the problem as a similar inference problem in Bayesian networks, overcoming some limitations of previous similar translations. In addition to making available the toolset of maximum-a-posteriori inference on Bayesian networks to sum-product networks, our reformulation also provides further insight into the connections of these two classes of models. The second approach casts the problem as a mixed-integer linear program, for which there exists very efficient solvers. This allows such inferences to be enriched with integer-linear constraints, increasing the expressivity of the models. We compare our reformulation approaches in a large collection of problems, and against state-of-the-art approaches. The results show that reformulation approaches are competitive.

关键词： Tractable Probabilistic Models Sum-Product Networks Probabilistic Circuits Maximuma-Posteriori Inference mixed-integer linear programming Bayesian Networks

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Decision Guidance on Software Feature Selection to Maximize the Benefit to Organizational Processes 22

Decision Guidance on Software Feature Selection to Maximize ...

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22nd International Conference on Enterprise Information Systems (ICEIS)

作者： Boccanera, Fernando Brodsky, Alexander George Mason Univ Comp Sci Dept Fairfax VA 22030 USA

ISBN: (纸本)9789897584237

Many software development projects fail because they do not deliver sufficient business benefit to justify the investment. Existing approaches to estimating business benefit of software adopt unrealistic assumptions which produce imprecise results. This paper focuses on removing this limitation for software projects that automate business workflow processes. For this class of projects, the paper proposes a new approach and a decision-guidance framework to select and schedule software features over a sequence of software releases as to maximize the net present value of the combined cash flow of software development as well as the improved organizational business workflow. The uniqueness of the proposed approach is in precise modelling of the business workflow and the savings achieved by deploying new software functionality.

关键词： Decision Guidance System Decision Support System Software Release Schedule Optimization mixed-integer linear programming

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On two-machine Flow Shop Scheduling Problem with disjoint setups 15

On two-machine Flow Shop Scheduling Problem with disjoint se...

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IEEE 15th International Conference of System of Systems Engineering (SoSE)

作者： Gnatowski, Andrzej Rudy, Jaroslaw Idzikowski, Radoslaw Wroclaw Univ Sci & Technol Dept Control Syst & Mechatron Wroclaw Poland Wroclaw Univ Sci & Technol Dept Comp Engn Wroclaw Poland

ISBN: (数字)9781728180502

ISBN: (纸本)9781728180502

We consider a variant of the Permutational Flow Shop Scheduling Problem with disjoint setups and makespan minimization. A mathematical model of the problem is presented and several properties on the feasibility of solutions are formulated. An elimination property is proposed, allowing to disregard up to 75% of the solution space. We also show an interesting connection between the number of feasible solutions and Catalan numbers. To solve the problem for a fixed job order, we propose two algorithms: mixed-integer linear programming exact formulation and a greedy heuristic algorithm. An empirical evaluation shows a promising efficiency of the heuristic, providing an optimal or near-optimal solutions for problem instances with low setup and job times time deviation.

关键词： discrete optimization disjoint setups flow shop problem mixed-integer linear programming

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Design of mosquito repellent molecules via the integration of hyperbox machine learning and computer aided molecular design

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DIGITAL CHEMICAL ENGINEERING 2022年 3卷

作者： Hatamleh, Mohamad Chong, Jia Wen Tan, Raymond R. Aviso, Kathleen B. Janairo, Jose Isagani B. Chemmangattuvalappil, Nishanth G. Univ Nottingham Malaysia Dept Chem & Environm Engn Broga Rd Semenyih 43500 Selangor De Malaysia De La Salle Univ Ctr Engn & Sustainable Dev Res 2401 Taft Ave Manila 0922 Philippines De La Salle Univ Dept Biol 2401 Taft Ave Manila 0922 Philippines

The use of mosquito repellents is an efficient way to prevent mosquito-borne diseases. Despite the accumulation of information about repellents, there remains the challenge of the lack of understanding of their mechanism of action. There is also a need for systematic methods for discovering new alternatives that mitigate the drawbacks of repellents currently in use. To address these research gaps, a computer-aided molecular design (CAMD) framework is developed for the optimal molecular design of mosquito repellents. In this framework, the mosquito repelling attribute of molecules are predicted using a data-driven hyperbox-based machine learning approach in the absence of a mechanistic prediction model. The best set of rules is selected from plausible alternative models developed. For the prediction of important physical properties, a group contribution-based method using reliable models is implemented. Subsequently, the CAMD formulation is developed as a mixed-integer linear programming model to obtain structures with minimum viscosity. Results show that of the structures generated, the hyperbox classifier correctly predicted the repelling ability of all molecules found to be known repellents in literature. The molecules not found in the databases provide key insights on where experimental research to develop new repellents should be targeted. Thus, this newly developed framework can be applied as a systematic technique to screen and narrow down the search space for candidate mosquito repellent molecules before final experimental verification.

关键词： Mosquito repellents Computer-aided molecular design Machine learning Hyperbox classifier Cheminformatics mixed-integer linear programming

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