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In view of the shortcomings of traditional multi-objective optimal methods, this paper introduces iSIGHT which is a kind of optimal design software. Based on optimal design framework Isight, the multi-objective optimal design method and step using the Neighborhood Cultivation Genetic Algorithm (NCGA) are investigated. Taking a multi-objective optimal design of spring as the example, the Pareto optimal...
We present an efficient genetic algorithm for mining multi-objective rules from large databases. Multi-objectives will conflict with each other, which makes it optimization problem that is very difficult to solve simultaneously. We propose a multi-objective evolutionary algorithm called improved niched Pareto genetic algorithm(INPGA), which not only accurate selects the candidates but also saves selection...
In this paper, a memetic meta-heuristic called the shuffled frog-leaping algorithm (SFLA) is presented for solving the combinatorial optimisation problem associated with lay-up sequence optimisation of laminate composite structures. The SFLA is a meta-heuristic optimization method that mimics the memetic evolution of a group of frogs when seeking for the location that has the maximum amount of available...
Quantum Evolutionary Algorithm (QEA) is an optimization algorithm based on the concept of quantum computing and Particle Swarm Optimization (PSO) algorithm is a population based intelligent search technique. Both these techniques have good performance to solve optimization problems. PSEQEA combines the PSO with QEA to improve the performance of QEA and it can solve single objective optimization problem...
Lifting body configuration is one of the typical layouts of Common Aero Vehicle(CAV), and the multi-objective optimization design of the airframe for lifting body configuration can greatly improve the integrated performance of Common Aero Vehicle. This paper establishes a numerical modeling of reentry vehicle to calculate these performance indexes such as the aerodynamic, the aerodynamic heating,...
Proper management of hospital inpatient admissions involves a large number of decisions that have complex and uncertain consequences for hospital resource utilization and patient flow. Further, inpatient admissions has a significant impact on the hospital's profitability, access, and quality of care. Making effective decisions to drive high quality, efficient hospital behavior is difficult, if not...
The selection of build orientation for a given part is one of the most important tasks encountered in the process planning phase of Layer Manufacturing in general and Stereolithography in particular. The orientation selection is by definition a multi-criteria optimization problem in which the operator seeks to achieve the optimum trade-off between cost and quality depending on the given fabrication...
The Network-on-Chip (NoC) synthesis problem consists in generating NoC topology to guarantee system design objectives such as: system performance and area. A novel multi-objective NoC synthesis solver is proposed to design application specific NoC of multi-stage topology. Based on NSGAII, a multi-objective genetic algorithm, the solver aims to supply multi-objective Pareto solutions set for the multiple...
In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-monetary variables. We enforce constraints which may not be as strict in reality. Based on a case in distributed energy production, we illustrate how we can avoid simplification by modeling multiple objectives, solving it with an NSGA-II...
Design of vertical section of hump pushing zone affects disconnecting capacity of marshalling yard. There are 2 factors being chosen to be the objective function, one is height difference between reception yard and hump crest, the other is the distance between the position of disconnecting the coupler of cars. Multi-objective optimization model is established. Meanwhile, Random weight multi-objective...
The problem of Web services selection based on quality of service (QoS) hasn't be essentially solved by the single objective optimal algorithm which optimizes service selection by aggregating multiple QoS parameters to form a composite objective function using weighted scoring method. This paper presents a Web services selection algorithm of QoS-aware and global multi-objective optimization, termed...
GA (genetic algorithm) approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. The GA optimization procedure converged to the global pare to front optimum for every case attempted, GA is able to find the global optimum results. This incentive extracting the data to the maximum extend possible to help designers to further...
One of the important issues in the design of fuzzy classifier is the formation of fuzzy if-then rules and the membership functions. This paper presents a Niched Pareto Genetic Algorithm (NPGA) approach to obtain the optimal rule-set and the membership function. To develop the fuzzy system the rule set and the membership functions are encoded into the chromosome and evolved simultaneously using NPGA...
The basic objective of economic dispatch of electric power generation is to schedule the committed generating unit outputs so as to meet the load demand at minimum operating cost while satisfying all unit and system equality and inequality constraints. Due to increasing concern over the environmental considerations, society demands adequate and secure electricity not only at the cheapest possible...
The cognitive radio (CR) has recently been proposed as one of the main opportunistic spectrum access solutions for dynamic spectrum allocation. In the CR context, an adaptive wireless node changes its transmission parameters to communicate efficiently and avoid interference with licensed users. In this paper, an adaptive pragmatic trellis coded modulation (TCM) scheme is proposed for CR systems. The...
A kind of unrelated parallel machines scheduling problem with fuzzy due dates is discussed. The memberships of fuzzy due dates denote the grades of satisfaction of decision-makers with respect to completion times with jobs. Objectives of scheduling are to maximize the minimum grade of satisfaction while makespan is minimized in the meantime. Nondominated Sorting Genetic Algorithm (NSGA-II) is employed...
This paper analyzed the unreasonable of widespread use of competitive selection rules to solving Constrained Optimization Genetic Algorithm. With the concept of Pareto dominance and the sequence of individual factorial design a new sort of population model. It balances the feasible region and constraints optimal solution search direction, which makes the Constrained Optimization Genetic Algorithm...
In this paper, a novel approach is proposed to solve the day-ahead multi-objective thermal generation scheduling problem. The proposed method combines the principles of Non-dominated Sorting Genetic Algorithm-II (NSGA-II) with problem specific crossover and mutation operators. Heuristics are used in the initial population by seeding the random population with a Priority list based solution for better...
Product Conceptual Design phase is the most important period, the process of scheme generation can be regarded as a progress of optimization in a state space. In this process, there are often conflicts between multiple objectives and multiple constraints, we can only produce a compromise set. Based on Technology Identification Evaluation and Selection method (TIES), constructing the mapping relations...
In this paper a new concept for the layout of hybrid-electric-powertrains is developed that includes optimization of the component-sizes as well as control strategies. In contrast to most existing publications, the approach explicitly considers the conflicting goals of low fuel consumption and high vehicle longitudinal dynamics and the trade-off is quantified. Two multiobjective optimization subproblems...
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