Genetic algorithm optimization for dynamic construction site layout planning

The dynamic construction site layout planning (DCSLP) problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic optimization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as safety and environmental considerations resulting from facilities’ operations and interconnections. The latter considerations are taken into account in the form of preferences or constraints regarding the proximity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP (for Nondeterministic Polynomial time)- hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. Several case studies and operational scenarios have been implemented through the Palisade’s Evolver software for model testing and evaluation. The results indicate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desirable preferences or constraints in the decision process

Single Tower Crane Allocation Models Using Ant Colony Optimization

The construction industry greatly benefits from the utilization of heavy machines and equipment to accomplish successful projects. Tower cranes, in specific, have a crucial role in the transportation of material loads across the site. Because these machines are fixed to the ground, it is essential for planners and managers to position them in a location that provides the most efficient transfer of materials possible. This is commonly known as the tower crane allocation problem, and many researchers have attempted to optimize the tower crane location using mathematical, artificial intelligence, and simulation approaches. However, many works from the literature contain critical errors which make the models infeasible. This research presents the application of ant colony optimization (ACO) and an ACO variation to tower crane allocation models. Results show that the approaches presented in this work are up to par with even the most powerful methodologies used to solve the problem

Structural optimization in steel structures, algorithms and applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Optimisation and Decision Support during the Conceptual Stage of Building Design

Merged with duplicate record 10026.1/726 on 28.02.2017 by CS (TIS)Modern building design is complex and involves many different disciplines operating in a fragmented manner. Appropriate computer-based decision support (DS) tools are sought that can raise the level of integration of different activities at the conceptual stage, in order to help create better designs solutions. This project investigates opportunities that exist for using techniques based upon the Genetic Algorithm (GA) to support critical activities of conceptual building design (CBD). Collective independent studies have shown that the GA is a powerful optimisation and exploratory search technique with widespread application. The GA is essentially very simple yet it offers robustness and domain independence. The GA efficiently searches a domain to exploit highly suitable information. It maintains multiple solutions to problems simultaneously and is well suited to non-linear problems and those of a discontinuous nature found in engineering design. The literature search first examines traditional approaches to supporting conceptual design. Existing GA techniques and applications are discussed which include pioneering studies in the field of detailed structural design. Broader GA studies are also reported which have demonstrated possibilities for investigating geometrical, topological and member size variation. The tasks and goals of conceptual design are studied. A rationale is introduced, aimed at enabling the GA to be applied in a manner that provides the most effective support to the designer. Numerical experiments with floor planning are presented. These studies provide a basic foundation for a subsequent design support system (DSS) capable of generating structural design concepts. A hierarchical Structured GA (SGA) created by Dasgupta et al [1] is investigated to support the generation of diverse structural design concepts. The SGA supports variation in the size, shape and structural configuration of a building and in the choice of structural frame type and floor system. The benefits and limitations of the SGA approach are discussed. The creation of a prototype DSS system, abritrarily called Designer-Pro (DPRO), is described. A detailed building design model is introduced which is required for design development and appraisal. Simplifications, design rationale and generic component modelling are mentioned. A cost-based single criteria optimisation problem (SCOP) is created in which other constraints are represented as design parameters. The thesis describes the importance of the object-oriented programming (OOP) paradigm for creating a versatile design model and the need for complementary graphical user interface (GUI) tools to provide human-computer interaction (HCI) capabilities for control and intelligent design manipulation. Techniques that increase flexibility in the generation and appraisal of concept are presented. Tools presented include a convergence plot of design solutions that supports cursor-interrogation to reveal the details of individual concepts. The graph permits study of design progression, or evolution of optimum design solutions. A visualisation tool is also presented. The DPRO system supports multiple operating modes, including single-design appraisal and enumerative search (ES). Case study examples are provided which demonstrate the applicability of the DPRO system to a range of different design scenarios. The DPRO system performs well in all tests. A parametric study demonstrates the potential of the system for DS. Limitations of the current approach and opportunities to broaden the study form part of the scope for further work. Some suggestions for further study are made, based upon newly-emerging techniques

Preventing premature convergence and proving the optimality in evolutionary algorithms

http://ea2013.inria.fr//proceedings.pdfInternational audienceEvolutionary Algorithms (EA) usually carry out an efficient exploration of the search-space, but get often trapped in local minima and do not prove the optimality of the solution. Interval-based techniques, on the other hand, yield a numerical proof of optimality of the solution. However, they may fail to converge within a reasonable time due to their inability to quickly compute a good approximation of the global minimum and their exponential complexity. The contribution of this paper is a hybrid algorithm called Charibde in which a particular EA, Differential Evolution, cooperates with a Branch and Bound algorithm endowed with interval propagation techniques. It prevents premature convergence toward local optima and outperforms both deterministic and stochastic existing approaches. We demonstrate its efficiency on a benchmark of highly multimodal problems, for which we provide previously unknown global minima and certification of optimality

Mapping the Practice of Site Layout Planning in the Construction Industry

Site Layout Planning (SLP) is a key activity for construction management and the overall success of construction projects. Past studies in this field have approached multiple techniques to solve SLP as a decision-making optimization problem. However, construction practitioners in the industry typically use intangible or subjective methods to plan the site layout, with the support of multiple tools that are not directly designed for planning construction sites. The mismatch between the available developments from research and actual methods approached in practice directed to the exploration of the practice of SLP conducted by practitioners to define the requirements needed in an SLP tool. Semi-structured interviews were conducted among forty-seven highly experienced construction practitioners who self-identified as fully responsible of SLP activities. Constructivist grounded theory and content analysis were used as the methodological basis to collect and analyze the data. From the analysis of 18635 transcript lines, 5028 codes were obtained, resulting in 190 labels, 60 categories, and 5 themes. The emergent themes describe the components of SLP as site characteristics, purpose, decision-making variables, tools and technology, and planning perspectives. The first part of the results details the practice of SLP, and the considerations and approaches taken by SLP practitioners when conducting a SLP, where the focus is to produce a functional site layout in the early stages of the project. The final part of the results presents the tools and functionalities that practitioners currently use to plan a site layout and highlights the need to integrate these functions and requirements into a single tool that can be practical for the construction industry. The requirements include resource properties and pairwise spatial relationships, planning documents and regulations, layout assessment metrics, and tool modules that facilitate addressing every stage of the planning as identified in the first part of the results. Finally, the aim of this study was to present a guideline for future developments in SLP to ensure their implementation in practical settings. This guideline was designed through the exploration of processes, needs, and requirements of the final users

Tilt Integral Derivative Controller Optimized by Battle Royale Optimization for Wind Generator Connected to Grid

Globally the countries are focusing on reducing the carbon footprint leading to a greater effort for electrical energy generation by renewable energy sources, particularly wind. The wind turbines are invariably using doubly fed asynchronous generator. In this paper a controller has been designed for a doubly fed induction motor. The proposed Tilt Integral Derivate controller for was compared with commonly used PI, PID controllers. Several optimization algorithms were used for tuning of controllers and the best one was selected for each type of controller. The controller has been optimized using battlefield optimization. It had been compared with proportional integral controller, fractional order proportional integral derivative controller. Other controllers were optimized using meta heuristic algorithms. The controller enhanced the system response in terms of settling time, rise time and other parameters. The Tilt controller gave the overall superior performance in terms of parameters like rise time, settling time, settling minimum, peak, and peak time. The results were obtained using MATLAB. This paper discusses operation of doubly fed induction motor operation and optimization methods