Strategies for multiobjective genetic algorithm development: Application to optimal batch plant design in process systems engineering

This work deals with multiobjective optimization problems using Genetic Algorithms (GA). A MultiObjective GA (MOGA) is proposed to solve multiobjective problems combining both continuous and discrete variables. This kind of problem is commonly found in chemical engineering since process design and operability involve structural and decisional choices as well as the determination of operating conditions. In this paper, a design of a basic MOGA which copes successfully with a range of typical chemical engineering optimization problems is considered and the key points of its architecture described in detail. Several performance tests are presented, based on the influence of bit ranging encoding in a chromosome. Four mathematical functions were used as a test bench. The MOGA was able to find the optimal solution for each objective function, as well as an important number of Pareto optimal solutions. Then, the results of two multiobjective case studies in batch plant design and retrofit were presented, showing the flexibility and adaptability of the MOGA to deal with various engineering problems

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

The method of multi-objective parametric design of magnetic field active canceling robust system for residential multy-story buildings closed to double-circuit overhead power lines

Aim. Development the method of multi-objective parametric design for robust system of active canceling of magnetic field based on binary preference relations of local objective for multi-objective minimax optimization problem. Methodology. Spatial location coordinates of the compensating winding and the current in the shielding winding were determined during the preference-based multi-objective parametric design of systems of active canceling based on solution of the vector minimax optimization, in whith the vector objective function calculated based on Biot-Savart's law. The solution of this vector minimax optimization problem calculated based on nonlinear Archimedes algorithm. Components of Jacobi matrix and Hesse matrix calculated based on multi-swarm multi-agent optimization. Results. Theoretically and experimentally confirmed the effectiveness of reducing the level of the magnetic field in residential multy-storey old building of a double-circuit overhead power transmission lines with a barrel-type arrangement of wires by means of active shielding with two compensation winding. Originality. The method of multi-objective parametric design for robust system of active canceling of magnetic field based on binary preference relations of local objective for multi-objective minimax optimization problem is developed. Practical value. It is shown the possibility to reduce the level of magnetic field in residential multy-storey old building closed to double-circuit overhead power transmission lines with a barrel-type arrangement of wires by means of system of active canceling with two canceling winding to a level safe for the population with an induction of 0.5 μT.Мета. Розробка методу багатокритеріального параметричного проектування системи активного екранування на основі бінарних відносин переваги локальних критеріїв векторної мінімаксної оптимізації. Методологія. Просторові координати розташування компенсаційних обмоток та струми в цих обмотках визначали під час багатокритеріального параметричного проектування системи активного екранування на основі бінарних відносин переваги векторної мінімаксної оптимізації, в якій векторна цільова функція розрахована на основі закона Біо-Савара. Рішення цієї задачи векторної мінімаксної оптимізації розраховано на основі нелінійного алгоритму Архімеда. Елементи матриць Якобі та Гессе розраховано на основі багаторойної багатоагентної оптимізації. Результати. Теоретично та експериментально підтверджена ефективність зниження рівня магнітного поля в житлових багатоповерхових приміщеннях старої забудови дволанцюгових повітряних ліній електропередачі з бочкоподібним розташуванням проводів за допомогою активного екранування з двома компенсаційними обмотками. Оригінальність. Розроблено метод багатокритеріального параметричного проектування системи активного екранування на основі бінарних відносин переваги локальних критеріїв векторної мінімаксної оптимізації. Практична цінність. Показана можливість зниження рівня магнітного поля в житлових багатоповерхових приміщеннях старої забудови дволанцюгових повітряних ліній електропередачі з бочкоподібним розташуванням проводів за допомогою активного екранування з двома компенсаційними обмотками до до безпечного для населення рівня з індуцією 0,5 μT

The method of multi-objective parametric design of magnetic field active canceling robust system for residential multy-story buildings closed to double-circuit overhead power lines

Aim. Development the method of multi-objective parametric design for robust system of active canceling of magnetic field based on binary preference relations of local objective for multi-objective minimax optimization problem. Methodology. Spatial location coordinates of the compensating winding and the current in the shielding winding were determined during the preference-based multi-objective parametric design of systems of active canceling based on solution of the vector minimax optimization, in whith the vector objective function calculated based on Biot-Savart's law. The solution of this vector minimax optimization problem calculated based on nonlinear Archimedes algorithm. Components of Jacobi matrix and Hesse matrix calculated based on multi-swarm multi-agent optimization. Results. Theoretically and experimentally confirmed the effectiveness of reducing the level of the magnetic field in residential multy-storey old building of a double-circuit overhead power transmission lines with a barrel-type arrangement of wires by means of active shielding with two compensation winding. Originality. The method of multi-objective parametric design for robust system of active canceling of magnetic field based on binary preference relations of local objective for multi-objective minimax optimization problem is developed. Practical value. It is shown the possibility to reduce the level of magnetic field in residential multy-storey old building closed to double-circuit overhead power transmission lines with a barrel-type arrangement of wires by means of system of active canceling with two canceling winding to a level safe for the population with an induction of 0.5 μT.Мета. Розробка методу багатокритеріального параметричного проектування системи активного екранування на основі бінарних відносин переваги локальних критеріїв векторної мінімаксної оптимізації. Методологія. Просторові координати розташування компенсаційних обмоток та струми в цих обмотках визначали під час багатокритеріального параметричного проектування системи активного екранування на основі бінарних відносин переваги векторної мінімаксної оптимізації, в якій векторна цільова функція розрахована на основі закона Біо-Савара. Рішення цієї задачи векторної мінімаксної оптимізації розраховано на основі нелінійного алгоритму Архімеда. Елементи матриць Якобі та Гессе розраховано на основі багаторойної багатоагентної оптимізації. Результати. Теоретично та експериментально підтверджена ефективність зниження рівня магнітного поля в житлових багатоповерхових приміщеннях старої забудови дволанцюгових повітряних ліній електропередачі з бочкоподібним розташуванням проводів за допомогою активного екранування з двома компенсаційними обмотками. Оригінальність. Розроблено метод багатокритеріального параметричного проектування системи активного екранування на основі бінарних відносин переваги локальних критеріїв векторної мінімаксної оптимізації. Практична цінність. Показана можливість зниження рівня магнітного поля в житлових багатоповерхових приміщеннях старої забудови дволанцюгових повітряних ліній електропередачі з бочкоподібним розташуванням проводів за допомогою активного екранування з двома компенсаційними обмотками до до безпечного для населення рівня з індуцією 0,5 μT

Engineering failure analysis and design optimisation with HiP-HOPS

The scale and complexity of computer-based safety critical systems, like those used in the transport and manufacturing industries, pose significant challenges for failure analysis. Over the last decade, research has focused on automating this task. In one approach, predictive models of system failure are constructed from the topology of the system and local component failure models using a process of composition. An alternative approach employs model-checking of state automata to study the effects of failure and verify system safety properties. In this paper, we discuss these two approaches to failure analysis. We then focus on Hierarchically Performed Hazard Origin & Propagation Studies (HiP-HOPS) - one of the more advanced compositional approaches - and discuss its capabilities for automatic synthesis of fault trees, combinatorial Failure Modes and Effects Analyses, and reliability versus cost optimisation of systems via application of automatic model transformations. We summarise these contributions and demonstrate the application of HiP-HOPS on a simplified fuel oil system for a ship engine. In light of this example, we discuss strengths and limitations of the method in relation to other state-of-the-art techniques. In particular, because HiP-HOPS is deductive in nature, relating system failures back to their causes, it is less prone to combinatorial explosion and can more readily be iterated. For this reason, it enables exhaustive assessment of combinations of failures and design optimisation using computationally expensive meta-heuristics. (C) 2010 Elsevier Ltd. All rights reserved

A Critical Review of Optimization Methods for Road Vehicles Design

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77078/1/AIAA-2006-6998-235.pd

Wind Energy and Multicriteria Analysis in Making Decisions on the Location of Wind Farms: A Case Study in the North-Eastern of Poland

This chapter presents an investigation of different methods of multicriteria analysis and different rules of proceedings that have to be taken into account for making decision about location of a wind farm with application in the north-eastern (NE) Poland. Ten multicriteria analyses were discussed taking into account the main criteria on which they are based on utility functions (MAUT, AHP, and DEMATEL), relationship outranking (ELECTRE, PROMETHEE, and ARROW-RAYNAUD), distances (TOPSIS), and decision support (BORDA ranking methods and their modified and COPELAND). Taking into account of nine criteria that should be met by the location of 15 wind turbines in Krynki and Szudzialowo communities, the main three criteria (C3, C8, and C9) were found to differentiate location of eight wind turbines (T-6–T-13), according to two variants (I and II). The Borda ranking method proved that from among the two variants considered, the more suitable location of wind turbines is second variant W II than first variant W I. Variant W II had a higher altitude of the terrain (C3) and less risk of impact on birds (C8) and bats species (C9) than variant W I

Evolutionary Multi-objective Optimization in Building Retrofit Planning Problem

AbstractEnergy efficiency has been a primary subject of concern in the building sector, which consumes the largest portion of the world's total energy. Especially for existing buildings, retrofitting has been regarded as the most feasible and cost-effective method to improve energy efficiency. When planning retrofit in public buildings, the most obvious objectives are to: (1) minimize energy consumption; (2) minimize CO2 emissions; (3) minimize retrofit costs; and (4) maximize thermal comfort; and one must consider these concerns together. The aim of this study is to apply evolutionary multi-objective optimization algorithm (NSGA-III) that can handle four objectives at a time to the application of building retrofit planning. A brief description of the algorithm is given, and the algorithm is examined using a building retrofit project, as a case study. The performance of the algorithm is evaluated using three measures: average distance to true Pareto-optimal front, hypervolume, and spacing. The results show that this study could be used to find a comprehensive set of trade-off scenarios for all possible retrofits, thereby providing references for building retrofit planners. These decision makers can then select the optimal retrofit strategy to satisfy stakeholders’ preferences

Evolutionary structural optimisation as a robust and reliable design tool

Evolutionary Structural Optimisation (ESO) is a relatively new design tool used to improve and optimise the design of structures. It is a heuristic method where a few elements of an initial design domain of finite elements are iteratively removed. Such a process is carried out repeatedly until an optimum design is achieved, or until a desired given area or volume is reached. There have been many contributions to the ESO procedure since its conception back in 1992. For example, a provision known as Bi-Directional ESO (BESO) has now been incorporated where elements may not only be removed, but added. Also, rather than deal with elements where they are either present or not, the designer now has the option to change the element's properties in a progressive fashion. This includes the modulus of elasticity, the density of the material and the thickness of plate elements, and is known as Morphing ESO. In addition to the algorithmic aspects of ESO, a large preference exists to optimise a structure based on a selection of criteria for various physical processes. Such examples include stress minimisation, buckling and electromagnetic problems. In a changing world that demands the enhancement of design tools and methods that incorporate optimisation, the development of methods like ESO to accommodate this demand is called for. It is this demand that this thesis seeks to satisfy. This thesis develops and examines the concept of multicriteria optimisation in the ESO process. Taking into account the optimisation of numerous criteria simultaneously, Multicriteria ESO allows a more realistic and accurate approach to optimising a model in any given environment. Two traditional methods � the Weighting method and the Global Criterion (Min-max) method have been used, as has two unconventional methods � the Logical AND method and the Logical OR method. These four methods have been examined for different combinations of Finite Element Analysis (FEA) solver types. This has included linear static FEA solver, the natural frequency FEA solver and a recently developed inertia FE solver. Mean compliance minimisation (stiffness maximisation), frequency maximisation and moment of inertia maximisation are an assortment of the specific objectives incorporated. Such a study has provided a platform to use many other criteria and multiple combinations of criteria. In extending the features of ESO, and hence its practical capabilities as a design tool, the creation of another optimisation method based on ESO has been ushered in. This method concerns the betterment of the bending and rotational performance of cross-sectional areas and is known as Evolutionary Moment of Inertia Optimisation (EMIO). Again founded upon a domain of finite elements, the EMIO method seeks to either minimise or maximise the rectangular, product and polar moments of inertia. This dissertation then goes one step further to include the EMIO method as one of the objectives considered in Multicriteria ESO as mentioned above. Most structures, (if not all) in reality are not homogenous as assumed by many structural optimisation methods. In fact, many structures (particularly biological ones) are composed of different materials or the same material with continually varying properties. In this thesis, a new feature called Constant Width Layer (CWL) ESO is developed, in which a distinct layer of material evolves with the developing boundary. During the optimisation process, the width of the outer surrounding material remains constant and is defined by the user. Finally, in verifying its usefulness to the practical aspect of design, the work presented herein applies the CWL ESO and the ESO methods to two dental case studies. They concern the optimisation of an anterior (front of the mouth) ceramic dental bridge and the optimisation of a posterior (back of the mouth) ceramic dental bridge. Comparisons of these optimised models are then made to those developed by other methods

Non-weighted aggregate evaluation function of multi-objective optimization for knock engine modeling

In decision theory, the weighted sum model (WSM) is the best known Multi-Criteria Decision Analysis (MCDA) approach for evaluating a number of alternatives in terms of a number of decision criteria. Assigning weights is a difficult task, especially if the number of criteria is large and the criteria are very different in character. There are some problems in the real world which utilize conflicting criteria and mutual effect. In the field of automotive, the knocking phenomenon in internal combustion or spark ignition engines limits the efficiency of the engine. Power and fuel economy can be maximized by optimizing some factors that affect the knocking phenomenon, such as temperature, throttle position sensor, spark ignition timing, and revolution per minute. Detecting knocks and controlling the above factors or criteria may allow the engine to run at the best power and fuel economy. The best decision must arise from selecting the optimum trade-off within the above criteria. The main objective of this study was to proposed a new Non-Weighted Aggregate Evaluation Function (NWAEF) model for non-linear multi-objectives function which will simulate the engine knock behavior (non-linear dependent variable) in order to optimize non-linear decision factors (non-linear independent variables). This study has focused on the construction of a NWAEF model by using a curve fitting technique and partial derivatives. It also aims to optimize the nonlinear nature of the factors by using Genetic Algorithm (GA) as well as investigate the behavior of such function. This study assumes that a partial and mutual influence between factors is required before such factors can be optimized. The Akaike Information Criterion (AIC) is used to balance the complexity of the model and the data loss, which can help assess the range of the tested models and choose the best ones. Some statistical tools are also used in this thesis to assess and identify the most powerful explanation in the model. The first derivative is used to simplify the form of evaluation function. The NWAEF model was compared to Random Weights Genetic Algorithm (RWGA) model by using five data sets taken from different internal combustion engines. There was a relatively large variation in elapsed time to get to the best solution between the two model. Experimental results in application aspect (Internal combustion engines) show that the new model participates in decreasing the elapsed time. This research provides a form of knock control within the subspace that can enhance the efficiency and performance of the engine, improve fuel economy, and reduce regulated emissions and pollution. Combined with new concepts in the engine design, this model can be used for improving the control strategies and providing accurate information to the Engine Control Unit (ECU), which will control the knock faster and ensure the perfect condition of the engine