Search results for "Fitness function"
showing 5 items of 15 documents
Genetic algorithms for 3d reconstruction with supershapes
2009
Supershape model is a recent primitive that represents numerous 3D shapes with several symmetry axes. The main interest of this model is its capability to reconstruct more complex shape than superquadric model with only one implicit equation. In this paper we propose a genetic algorithms to re-construct a point cloud using those primitives. We used the pseudo-Euclidean distance to introduce a threshold to handle real data imperfection and speed up the process. Simulations using our proposed fitness functions and a fitness function based on inside-outside function show that our fitness function based on the pseudo-Euclidean distance performs better.
Solving a continuous periodic review inventory-location allocation problem in vendor-buyer supply chain under uncertainty
2019
In this work, a mixed-integer binary non-linear two-echelon inventory problem is formulated for a vendor-buyer supply chain network in which lead times are constant and the demands of buyers follow a normal distribution. In this formulation, the problem is a combination of an (r, Q) and periodic review policies based on which an order of size Q is placed by a buyer in each fixed period once his/her on hand inventory reaches the reorder point r in that period. The constraints are the vendors’ warehouse spaces, production restrictions, and total budget. The aim is to find the optimal order quantities of the buyers placed for each vendor in each period alongside the optimal placement of the ve…
A Preference-Based Evolutionary Algorithm for Multi-Objective Optimization
2009
In this paper, we discuss the idea of incorporating preference information into evolutionary multi-objective optimization and propose a preference-based evolutionary approach that can be used as an integral part of an interactive algorithm. One algorithm is proposed in the paper. At each iteration, the decision maker is asked to give preference information in terms of his or her reference point consisting of desirable aspiration levels for objective functions. The information is used in an evolutionary algorithm to generate a new population by combining the fitness function and an achievement scalarizing function. In multi-objective optimization, achievement scalarizing functions are widel…
An evolutionary approach to multi-objective scheduling of mixed model assembly lines
1999
In this paper a multi-objective genetic algorithm for the scheduling of a mixed model assembly line is proposed, pursuing the line stop time minimisation together with the component usage smoothing. Specific features of the developed GA are step by step random selection of diversified crossover and mutation operators, population control for the substitution of duplicate chromosomes, and in-process updating of GA control parameters. Three different formulation of the fitness function were been tested with some distinct line configurations.
A Workflow for the Performance Based Design of Naturally Ventilated Tall Buildings Using a Genetic Algorithm (GA)
2019
Optimization of Natural Ventilation process in highrise buildings is one of the most complex and least addressed phenomenon in the field of sustainable architecture. This issue requires urgent consideration to reduce the computation time due to fast growing demand of vertical construction in metropolitan cities. Until recently most highrise buildings have been operated with mechanical systems, causing high energy loads in hot climates and have high carbon footprints. Highrise buildings with natural ventilation and sky gardens can address these problems. This study involves the development of a Genetic Algorithm (GA) addressing the multi objective optimization of natural ventilation in tall …