Modeling without categorical variables: a mixed-integer nonlinear program for the optimization of thermal insulation systems

2010 ◽  
Vol 11 (2) ◽  
pp. 185-212 ◽  
Author(s):  
Kumar Abhishek ◽  
Sven Leyffer ◽  
Jeffrey T. Linderoth
Keyword(s):  
Thermal Insulation ◽  
Mixed Integer ◽  
Categorical Variables ◽  
Nonlinear Program ◽  
Insulation Systems

scholarly journals The Analysis of Small Investors’ Demands on a Thermal Insulation System for a Family House: A Case Study

2021 ◽  
Vol 13 (5) ◽  
pp. 2491
Author(s):  
Alena Tažiková ◽  
Zuzana Struková ◽  
Mária Kozlovská
Keyword(s):  
Decision Making ◽  
Thermal Insulation ◽  
Construction Cost ◽  
Environmental Cost ◽  
Multi Criteria Decision Making ◽  
Insulation System ◽  
Insulation Systems ◽  
Small Investors ◽  
The Cost ◽  
Family House

This study deals with small investors’ demands on thermal insulation systems when choosing the most suitable solution for a family house. By 2050, seventy percent of current buildings, including residential buildings, are still expected to be in operation. To reach carbon neutrality, it is necessary to reduce operational energy consumption and thus reduce the related cost of building operations and the cost of the life cycle of buildings. One solution is to adapt envelopes of buildings by proper insulation solutions. To choose an optimal thermal insulation system that will reduce energy consumption of building, it is necessary to consider the environmental cost of insulation materials in addition to the construction cost of the materials. The environmental cost of a material depends on the carbon footprint from the initial origin of the material. This study presents the results of a multi-criteria decision-making analysis, where five different contractors set the evaluation criteria for selection of the optimal thermal insulation system. In their decision-making, they involved the requirements of small investors. The most common requirements were selected: the construction cost, the construction time (represented by the total man-hours), the thermal conductivity coefficient, the diffusion resistance factor, and the reaction to fire. The confidences of the criteria were then determined with the help of the pairwise comparison method. This was followed by multi-criteria decision-making using the method of index coefficients, also known as the method of basic variant. The multi-criteria decision-making included thermal insulation systems based on polystyrene, mineral wool, thermal insulation plaster, and aerogels’ nanotechnology. As a result, it was concluded that, currently, in Slovakia, small investors emphasize the cost of material and the coefficient of thermal conductivity and they do not care as much about the carbon footprint of the material manufacturing, the importance of which is mentioned in this study.

Transit Planning Optimization Under Ride-Hailing Competition and Traffic Congestion

2021 ◽  
Author(s):  
Keji Wei ◽  
Vikrant Vaze ◽  
Alexandre Jacquillat
Keyword(s):  
New York ◽  
Traffic Congestion ◽  
Service Providers ◽  
Public Transit ◽  
Mixed Integer ◽  
Nonlinear Program ◽  
Transit Planning ◽  
Planning Optimization ◽  
Transit Ridership ◽  
Transit Agencies

With the soaring popularity of ride-hailing, the interdependence between transit ridership, ride-hailing ridership, and urban congestion motivates the following question: can public transit and ride-hailing coexist and thrive in a way that enhances the urban transportation ecosystem as a whole? To answer this question, we develop a mathematical and computational framework that optimizes transit schedules while explicitly accounting for their impacts on road congestion and passengers’ mode choice between transit and ride-hailing. The problem is formulated as a mixed integer nonlinear program and solved using a bilevel decomposition algorithm. Based on computational case study experiments in New York City, our optimized transit schedules consistently lead to 0.4%–3% system-wide cost reduction. This amounts to rush-hour savings of millions of dollars per day while simultaneously reducing the costs to passengers and transportation service providers. These benefits are driven by a better alignment of available transportation options with passengers’ preferences—by redistributing public transit resources to where they provide the strongest societal benefits. These results are robust to underlying assumptions about passenger demand, transit level of service, the dynamics of ride-hailing operations, and transit fare structures. Ultimately, by explicitly accounting for ride-hailing competition, passenger preferences, and traffic congestion, transit agencies can develop schedules that lower costs for passengers, operators, and the system as a whole: a rare win–win–win outcome.

scholarly journals Integration of Mixed-Integer Nonlinear Program and Project Management Tool to Support Sustainable Cost-Optimal Construction Scheduling

2021 ◽  
Vol 13 (21) ◽  
pp. 12173
Author(s):  
Borna Dasović ◽  
Uroš Klanšek
Keyword(s):  
Project Management ◽  
Optimal Schedule ◽  
Indirect Costs ◽  
Management Tool ◽  
Mixed Integer ◽  
Task Completion ◽  
Nonlinear Program ◽  
Project Schedule ◽  
Construction Scheduling ◽  
Optimal Construction

This paper presents the integration of mixed-integer nonlinear program (MINLP) and project management tool (PMT) to support sustainable cost-optimal construction scheduling. An integrated structure of a high-level system for exact optimization and PMT was created. To ensure data compatibility between the optimization system and PMT and to automate the process of obtaining a cost-optimal schedule, a data transformation tool (DTT) was developed within a spreadsheet application. The suggested system can determine: (i) an optimal project schedule with associated network diagram and Gantt chart in continuous or discrete time units; (ii) optimal critical and non-critical activities, including their early start, late start, early finish, late finish along with total and free slack times; and (iii) minimum total project cost along with the allocation of direct and indirect costs. The system provides functionalities such as: (i) MINLP can be updated, and schedules can be re-optimized; (ii) the optimal schedule can be saved as a baseline to track changes; (iii) different optimization algorithms can be engaged whereby switching between them does not require model changes; (iv) PMT can be used to track task completion in the optimized schedule; (v) calendar settings can be changed; and (vi) visual reports can be generated to support efficient project management. Results of cost-optimal project scheduling are given in a conventional PMT environment, which raises the possibility that the proposed system will be more widely used in practice. Integration of MINLP and PMT allows each software to be used for what it was initially designed. Their combination leads to additional information and features of optimized construction schedules that would be significantly more difficult to achieve if used separately. Application examples are given in the paper to show the advantages of the proposed approach.

Generalized Field-Development Optimization With Derivative-Free Procedures

SPE Journal ◽  
2014 ◽  
Vol 19 (05) ◽  
pp. 891-908 ◽  
Author(s):  
Obiajulu J. Isebor ◽  
David Echeverría Ciaurri ◽  
Louis J. Durlofsky
Keyword(s):  
Computational Cost ◽  
Optimization Method ◽  
Optimal Number ◽  
Global Search ◽  
Search Method ◽  
Pattern Search ◽  
Mixed Integer ◽  
Categorical Variables ◽  
Field Development ◽  
Derivative Free

Summary The optimization of general oilfield development problems is considered. Techniques are presented to simultaneously determine the optimal number and type of new wells, the sequence in which they should be drilled, and their corresponding locations and (time-varying) controls. The optimization is posed as a mixed-integer nonlinear programming (MINLP) problem and involves categorical, integer-valued, and real-valued variables. The formulation handles bound, linear, and nonlinear constraints, with the latter treated with filter-based techniques. Noninvasive derivative-free approaches are applied for the optimizations. Methods considered include branch and bound (B&B), a rigorous global-search procedure that requires the relaxation of the categorical variables; mesh adaptive direct search (MADS), a local pattern-search method; particle swarm optimization (PSO), a heuristic global-search method; and a PSO-MADS hybrid. Four example cases involving channelized-reservoir models are presented. The recently developed PSO-MADS hybrid is shown to consistently outperform the standalone MADS and PSO procedures. In the two cases in which B&B is applied, the heuristic PSO-MADS approach is shown to give comparable solutions but at a much lower computational cost. This is significant because B&B provides a systematic search in the categorical variables. We conclude that, although it is demanding in terms of computation, the methodology presented here, with PSO-MADS as the core optimization method, appears to be applicable for realistic reservoir development and management.

scholarly journals Impact resistance of external thermal insulation systems

2018 ◽  
Vol 163 ◽  
pp. 08004 ◽  
Author(s):  
Ewa Sudoł ◽  
Dawid Dębski ◽  
Renata Zamorowska ◽  
Barbara Francke
Keyword(s):  
Thermal Insulation ◽  
Impact Resistance ◽  
Experimental Program ◽  
Insulation Material ◽  
Test Results ◽  
Composite Systems ◽  
Factors Influencing ◽  
Insulation Systems ◽  
The Impact ◽  
Fibre Mesh

In the paper the results of an experimental program intended to determine factors influencing the impact resistance of the External Thermal Insulation Composite Systems (ETICS) were presented. For the research the systems based on polystyrene have been chosen. The insulation material was faced with a rendering consisting of base coat reinforced with standard or armored glass fibre mesh and silicone or silicone-silicate binders as finishing coats. The influence of various renderings components was evaluated with respect to resistance to hard body impact and resistance to hail. The test results were discussed in the context of the possible impact level on ETICS in use.

Flexible Synthesis of Heat Exchanger Network with Particle Swarm Optimization Algorithm

2011 ◽  
Vol 214 ◽  
pp. 569-572 ◽  
Author(s):  
Xio Ling Zhang ◽  
Hong Chao Yin ◽  
Zhao Yi Huo
Keyword(s):  
Particle Swarm Optimization ◽  
Heat Exchanger ◽  
Operating Cost ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Nonlinear Program ◽  
Heat Exchanger Network ◽  
Swarm Optimization

In this paper, the flexible synthesis problem for heat exchanger network(HEN) is formulated to a mixed integer nonlinear program(MINLP) model. The objection function of the model consists of two components: First, a candidate HEN structure has to satisfy flexible criterion during input span. Second, a minimized annual cost consisting of investment cost and operating cost is investigated. The solution strategy based on particle swarm optimization(PSO) algorithm is proposed to obtain the optimal solution of the presented model. Finally, a four streams example is investigated to show the advantage of the whole proposed optimization approach.

Sign in / Sign up

Export Citation Format

Share Document