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Constraint-based adaptation for complex space configuration in building services
In this paper an object-based CAD programming is used to take advantage of standardization to handle the schematic design, sizing and layout planning for ceiling mounted fan coil system in a building ceiling void. In order to deal with more complex geometry and real building size, we have used a hybrid approach combining case-based reasoning and constraint programming techniques. Very often, building services engineers use previous solutions and adapt them to new problems. Case-based reasoning mirrors this practical approach and did help us deal effectively with increasingly complex geometry. Our approach combines automation and interactivity. From the specification of the building 3D BIM model, our software prototype proceeds through four steps. First, the user divides the building into zones, each zone being defined by a geometrical primitive (i.e. rectangle zone, triangle zone, curved zone, etc.). Next, for each zone a similar case is retrieved from the case library. The retrieval process will generate a first incomplete 3D solution containing some inconsistencies. Next, the incomplete solution is adapted, using constraint programming techniques, to provide a consistent solution. Finally, distribution routes (i.e. ducts and pipes) are generated using constraint programming techniques. The 3D fan coil solution can be modified or improved by the designer, while providing further contribution by concentrating on interactivity. The project has been funded by the Engineering and Physical Sciences Research Council (EPSRC) in the UK
Facility layout problem: Bibliometric and benchmarking analysis
Facility layout problem is related to the location of departments in a facility area, with the aim of determining the most effective configuration. Researches based on different approaches have been published in the last six decades and, to prove the effectiveness of the results obtained, several instances have been developed. This paper presents a general overview on the extant literature on facility layout problems in order to identify the main research trends and propose future research questions. Firstly, in order to give the reader an overview of the literature, a bibliometric analysis is presented. Then, a clusterization of the papers referred to the main instances reported in literature was carried out in order to create a database that can be a useful tool in the benchmarking procedure for researchers that would approach this kind of problems
Shaper-GA: automatic shape generation for modular housing
This work presents an automatic system that, from the specification of an architectural
language of design, generates several alternative floor plants for the construction of
modular homes.
The system uses Genetic Algorithms and is capable of efficiently producing various
plant solutions. The rules of architecture are implemented in the fitness function translating
the rules of a Shape Grammar created by the architect.
Different solutions of feasible plants are generated, that is, solutions that obey the rules
of Shape Grammar and do not have overlays between the rooms. The system can be
integrated with a user-friendly interface in the future, to allow for the house owners
customization of their own house. Such a tool can also be delivered to construction
companies for them to manage the design of modular houses that meet specific clients
requirements.Este trabalho apresenta um sistema automático que, a partir da especificação de uma
linguagem arquitetural de design, gera plantas alternativas para residências de construção
modular.
O sistema usa Algoritmos Genéticos e é capaz de produzir várias soluções de plantas
de modo eficiente. As regras de arquitetura são implementadas na função de fitness a partir
de uma Gramática de Forma criada pelo arquiteto.
São geradas diferentes soluções de plantas exequíveis, isto é, soluções que obedecem à
Gramática de Forma e não têm sobreposições entre as suas divisões. Pode ser futuramente
integrado com uma interface amigável para o utilizador de forma a que este personalize e
crie a sua futura casa. Tal ferramenta pode também ser entregue às companhias de
construção de forma a que estas gerem uma planta para uma casa modular personalizada
High-Level Object Oriented Genetic Programming in Logistic Warehouse Optimization
Disertační práce je zaměřena na optimalizaci průběhu pracovních operací v logistických skladech a distribučních centrech. Hlavním cílem je optimalizovat procesy plánování, rozvrhování a odbavování. Jelikož jde o problém patřící do třídy složitosti NP-težký, je výpočetně velmi náročné nalézt optimální řešení. Motivací pro řešení této práce je vyplnění pomyslné mezery mezi metodami zkoumanými na vědecké a akademické půdě a metodami používanými v produkčních komerčních prostředích. Jádro optimalizačního algoritmu je založeno na základě genetického programování řízeného bezkontextovou gramatikou. Hlavním přínosem této práce je a) navrhnout nový optimalizační algoritmus, který respektuje následující optimalizační podmínky: celkový čas zpracování, využití zdrojů, a zahlcení skladových uliček, které může nastat během zpracování úkolů, b) analyzovat historická data z provozu skladu a vyvinout sadu testovacích příkladů, které mohou sloužit jako referenční výsledky pro další výzkum, a dále c) pokusit se předčit stanovené referenční výsledky dosažené kvalifikovaným a trénovaným operačním manažerem jednoho z největších skladů ve střední Evropě.This work is focused on the work-flow optimization in logistic warehouses and distribution centers. The main aim is to optimize process planning, scheduling, and dispatching. The problem is quite accented in recent years. The problem is of NP hard class of problems and where is very computationally demanding to find an optimal solution. The main motivation for solving this problem is to fill the gap between the new optimization methods developed by researchers in academic world and the methods used in business world. The core of the optimization algorithm is built on the genetic programming driven by the context-free grammar. The main contribution of the thesis is a) to propose a new optimization algorithm which respects the makespan, the utilization, and the congestions of aisles which may occur, b) to analyze historical operational data from warehouse and to develop the set of benchmarks which could serve as the reference baseline results for further research, and c) to try outperform the baseline results set by the skilled and trained operational manager of the one of the biggest warehouses in the middle Europe.
Genetic Programming + Unfolding Embryology in Automated Layout Planning
Automated layout planning aims to the implementation of computational methods for the generation and the optimization of floor plans, considering the spatial configuration and the assignment of activities. Sophisticated strategies such as Genetic Algorithms have been implemented as heuristics of good solutions. However, the generative forces that derive from the social structures have been often neglected. This research aims to illustrate that the data that encode the layout’s social and cultural generative forces, can be implemented within an evolutionary system for the design of residential layouts. For that purpose a co-operative system was created, which is composed of a Genetic Programming algorithm and an agent-based unfolding embryology procedure that assigns activities to the spaces generated by the GP algorithm. The assignment of activities is a recursive process which follows instructions encoded as permeability graphs. Furthermore, the Ranking Sum Fitness evaluation method is proposed and applied for the achievement of multi-objective optimization. Its efficiency is tested against the Weighted-Sum Fitness function. The system’s results, both numerical and spatial, are compared to the results of a conventional evolutionary approach. This comparison showed that, in general, the proposed system can yield better solutions
Shaper-GA: automatic shape generation for modular house design
This work presents a Genetic Algorithm (GA) approach to produce automatic designs for modular houses: Shaper-GA. A set of architectural design rules defining a language of design is incorporated into the GA fitness function. When possible genetic drift or local convergence might be occurring, the method starts an adaptive mutation rate to overcome fitness stagnation. The GA tool efficiently produces several layout solutions obeying the design rules and further placement constraints. Such a tool can be integrated into an appropriate user interface allowing future house
owners to customize their own house or construction companies to answer client's' requirements while complying with a language of design.info:eu-repo/semantics/acceptedVersio
Parametric freeform-based construction site layout optimization
Traditional approaches to the construction site layout problem have been focused mainly on rectilinear facilities where the importance proximity measures are mainly based on Cartesian distances between the centroids of the facilities. This is a fair abstraction of the problem; however it ignores the fact that many facilities on construction sites assume non-rectilinear shapes that allow for better compaction within tight sites. The main focus of this research is to develop a new approach of modeling site facilities to surpass limitations and inefficiencies of previous models and to ensure a more realistic approach to construction site layout problems. A construction site layout optimization model was developed that can suit both static and dynamic site layouts. The developed model is capable of modeling any rectilinear and non-rectilinear site shapes, especially splines, since it utilizes a parametric modeling software. The model also has the ability to mimic the “dynamic” behavior of the objects’ shapes through the introduction and development of three different algorithms for dynamic shapes; where the geometrical shapes representing site facilities automatically modify their geometrical forms to fit in strict areas on site. Moreover, the model provides different proximity measures and distance measurement techniques rather than the normal centroidal Cartesian distances used in most models. The new proximity measures take into consideration actual movement between the facilities including any passageways or access roads on site. Furthermore, the concept of selective zoning was introduced and a corresponding algorithm was provided; where the concept significantly enhances optimization efficiency by minimizing the number of solutions through selection of pre-determined movement zones on site. Soft constraints for buffer zones around the site facilities were developed as well. The site layout modeling was formulated on commercial parametric modeling tools (Rhino® and Grasshopper®) and the optimization was performed through genetic algorithms. After each of the algorithms was verified and validated, a case study of a real dynamic site layout planning problem was made to validate the comprehensive model combining all of the modules together. Different proximity measures and distance measurement techniques were considered, along with different static and dynamic geometrical shapes for the temporary facilities. The model produced valid near-optimum solutions, a comparison was then made between the layout that is produced with the model and the layout that would have been produced by other models to demonstrate the capabilities and advantages of the produced model
An Object-Based Evolutionary Algorithm for Solving Rectangular Piece Nesting Problems
Nesting problems have been tackled by researchers using a vast number of algorithms in the past. Most of the algorithms, however, need to perform on a one-dimensional space. Therefore, the problem must be transformed into a one-dimensional space problem similar to the travelling salesman problem. Consequently, loss of solutions due to the dimensional reduction may occur. In this study, an object-based evolutionary algorithm for rectangular piece nesting problems is proposed. This methodology is created on truly two-dimensional space, allowing new mechanisms (i.e., individual representation, initialization, etc.) and new object-based genetic operators (i.e., hill-climbing, mutation, and recombination operators) to perform effectively on the space. Since no dimensional reduction is used, therefore, no solution losses during the searching. Simulation/animation of the layouts shows the continual improvement by using this method over generations. Experimental results are promising
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