Search results for "MULTI-OBJECTIVE OPTIMISATION"
showing 9 items of 9 documents
MULTI-OBJECTIVE OPTIMISATION OF BUILDINGS AND BUILDING CLUSTERS PERFORMANCE: A LIFE CYCLE THINKING APPROACH
2021
INTERNAL PRESSURE AND COUNTERPUNCH ACTION DESIGN IN Y-SHAPED TUBE HYDROFORMING PROCESSES: A MULTI OBJECTIVE OPTIMISATION APPROACH
2009
In sheet metal forming most of the problems are multi-objective problems, generally characterised by conflicting objectives. A classical approach to investigate such kind of problems is focused on a combination of multiple objectives into a unique objective function to be optimised. Actually, in metal forming processes optimisation two main phases have to be developed in order to reach an optimal solution: the former is the modelling phase (definition of the design variables and objective function) and the latter concerns the computational aspect (numerical simulations or experiment to be developed). In this paper, an integration between numerical simulations, response surface methodology a…
Design of complex sheet metal forming processes: a new computer aided progressive approach
2010
The growing interest in sheet metal stamping processes, particularly in automotive industry, led to three main issues in this field: request of very complex shapes; growing interest in springback control; solution of multi-objective problems. This makes the design of the sheet metal stamping processes very difficult, since the number of both design variables and design objectives are progressively increased; therefore, proper design methodologies to reduce times and costs are highly required. In this paper, an innovative design approach able to manage and optimize complex stamping operations is proposed. In particular, a progressive design approach based on the integration between numerical…
Smart multi-carrier energy system: Optimised energy management and investment analysis
2016
This paper proposes an optimised Energy Management System for a multi-carrier hub, which integrates two energy distribution networks, for hydrogen and electricity. The economic sustainability of a real-life instantiation of such a system has been analysed as well. The Energy Management System has been developed by means of a multi-objective optimisation algorithm, the Non-dominated Sorting Genetic Algorithm II, implemented using MATLAB®. The achieved results consist in a series of set-points defining the working conditions of the plant for a chosen time horizon. Data provided by this process also show the effectiveness of the adopted optimisation approach. The financial analysis is performe…
Discovering the Discriminating Power in Patient Test Features Using Visual Analytics: A Case Study in Parkinson’s Disease
2016
Part 11: New Methods and Tools for Big Data Wokshop (MT4BD); International audience; This paper presents a novel methodology for selecting the most representative features for identifying the presence of the Parkinson’s Disease (PD). The proposed methodology is based on interactive visual analytic based on multi-objective optimisation. The implemented tool processes and visualises the information extracted via performing a typical line-tracking test using a tablet device. Such output information includes several modalities, such as position, velocity, dynamics, etc. Preliminary results depict that the implemented visual analytics technique has a very high potential in discriminating the PD …
Multi-objective human resources allocation in R&D projects planning
2009
In a R&D department, several projects may have to be implemented simultaneously within a certain period of time by a limited number of human resources with diverse skills. This paper proposes an optimisation model for the allocation of multi-skilled human resources to R&D projects, considering individual workers as entities having different knowledge, experience and ability. The model focuses on three fundamental aspects of human resources: the different skill levels, the learning process and the social relationships existing in working teams. The resolution approach for the multi-objective problem consists of two steps: firstly, a set of non-dominated solutions is obtained by exploring the…
A Matrix Model For An Energy Management System Based On Multi-Carrier Energy Hub Approach
2015
The INGRID FP7 European co-funded project studies several methodologies concerning hydrogen production and storage, aiming to provide services to electricity system operators for suitably balancing electrical supply and demand. In such a context, the problem of integrating different carriers into a single multi-hub optimiser represents a challenging topic for the research. This paper depicts the Energy Management System (EMS) of the plant which will be developed and built as a prototype of the INGRID system. The approach followed for the EMS design and development takes the cue from the matrix model presented in the rest of the paper, as well as the general optimisation problem formulation …
A multi-objective Pareto design approach for simultaneous control of thinning and springback in complex stamping operations.
2009
Abstract In sheet metal forming operations design, optimization problems have to be solved in order to reach optimal process conditions. In these problems, there are some crucial issues to be taken into account: - most of the problems are multi objective problems, generally characterized by conflicting objectives: the definition of proper parameters aimed to prevent both springback and fracture is a typical example of an optimization problem in sheet metal forming characterized by conflicting goals; - in an industrial environment a great interest would be focused on the availability of a cluster of possible optimal solutions instead of a single “almost optimal” solution. Taking into account…
Exact extension of the DIRECT algorithm to multiple objectives
2019
The direct algorithm has been recognized as an efficient global optimization method which has few requirements of regularity and has proven to be globally convergent in general cases. direct has been an inspiration or has been used as a component for many multiobjective optimization algorithms. We propose an exact and as genuine as possible extension of the direct method for multiple objectives, providing a proof of global convergence (i.e., a guarantee that in an infinite time the algorithm becomes everywhere dense). We test the efficiency of the algorithm on a nonlinear and nonconvex vector function. peerReviewed