Design and comparison of two evolutionary approaches for automated product design

Matei, Oliviu; Contras, Diana; Pop, Petrică C.; VźLean, Honoriu

doi:10.1007/s00500-016-2292-x

Cited by 3 publications

(4 citation statements)

References 35 publications

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“…PC set F for the fixed winch hoist was obtained by product investigation, customer-requirement analysis, technical, economic, and social environments, and, finally, an expert team. Given F = { 1 low complexity, 2 manufacturability, 3 assembly ability, 4 reliability, 5 mechanical strength 6 environment-friendly, 7 brake, 8 low noise, 9 Lifting stability, 10 low cost, 11 synchronicity, 12 high energy-conversion efficiency, and 13 lightweight}. How to express and implement the element-matter model of a fixed winch hoist is introduced below.…”

Section: Case Studymentioning

confidence: 99%

“…Ming-Chyuan et al [12] proposed an integrated procedure that involves neural-network training and genetic-algorithm simulations within the Taguchi quality-design process to aid in searching for an optimal solution with more precise design-parameter values for improving product development. Oliviu Matei et al [13] addressed the automated product-design problem with two distinct evolutionary approaches: genetic algorithms and evolutionary ontology. S.H.…”

mentioning

confidence: 99%

“…S.H. Ling [14] developed intelligent particle-swarm optimization (iPSO), where a fuzzy-logic system, developed based on human knowledge, is proposed to determine the inertia weight for the swarm movement of the PSO and the control parameter of a newly introduced cross-mutated operation.Although the above methods greatly contribute to the process of conceptual-design intelligence, the main focus is to study the commonality of various problem models [4,6,13,14]. While the model can be solved to obtain a feasible solution, they ignore the personality of the problem.…”

mentioning

confidence: 99%

“…Although the above methods greatly contribute to the process of conceptual-design intelligence, the main focus is to study the commonality of various problem models [4,6,13,14]. While the model can be solved to obtain a feasible solution, they ignore the personality of the problem.…”

mentioning

confidence: 99%

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A Product Conceptual Design Method Based on Evolutionary Game

Huo

Chen

et al. 2019

Machines

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In this paper, an intelligent-design method to deal with conceptual optimization is proposed for the decisive impact of the concept on the product-development cycle cost and performance. On the basis of matter-element analysis, an effective functional-structure combination model satisfying multiple constraints is first established, which maps the product characteristics obtained by expert research and customer-requirements analysis of the function and structure domain. Then, the Evolutionary Game Algorithm (EGA) was utilized to solve the model, in which a strategy-combination space is mapped to the solution-search space of the conceptual-solution problem, and the game-utility function is mapped to the objective functions of concept evaluation. Constant disturbance and Best-Response Correspondence were applied cross-repeatedly until the optimal equilibrium Pareto state corresponding to the global optimal solution was obtained. Finally, the method was simulated on MATLAB 8.3 and applied to the design for fixed winch hoist, which greatly shortens its design cycle.

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Section: Case Studymentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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A Product Conceptual Design Method Based on Evolutionary Game

Huo

Chen

et al. 2019

Machines

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Hybrid hierarchical fuzzy group decision-making based on information axioms and BWM: Prototype design selection

Maghsoodi

Mosavat

Hafezalkotob

et al. 2019

Computers & Industrial Engineering

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Hybrid Assembly Path Planning for Complex Products by Reusing a Priori Data

Zhou

Cao

et al. 2021

Mathematics

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Assembly path planning (APP) for complex products is challenging due to the large number of parts and intricate coupling requirements. A hybrid assembly path planning method is proposed herein that reuses a priori paths to improve the efficiency and success ratio. The assembly path is initially segmented to improve its reusability. Subsequently, the planned assembly paths are employed as a priori paths to establish an a priori tree, which is expanded according to the bounding sphere of the part to create the a priori space for path searching. Three rapidly exploring random tree (RRT)-based algorithms are studied for path planning based on a priori path reuse. The RRT* algorithm establishes the new path exploration tree in the early planning stage when there is no a priori path to reuse. The static RRT* (S-RRT*) and dynamic RRT* (D-RRT*) algorithms form the connection between the exploration tree and the a priori tree with a pair of connection points after the extension of the exploration tree to a priori space. The difference between the two algorithms is that the S-RRT* algorithm directly reuses an a priori path and obtains a new path through static backtracking from the endpoint to the starting point. However, the D-RRT* algorithm further extends the exploration tree via the dynamic window approach to avoid collision between an a priori path and obstacles. The algorithm subsequently obtains a new path through dynamic and non-continuous backtracking from the endpoint to the starting point. A hybrid process combining the RRT*, S-RRT*, and D-RRT* algorithms is designed to plan the assembly path for complex products in several cases. The performances of these algorithms are compared, and simulations indicate that the S-RRT* and D-RRT* algorithms are significantly superior to the RRT* algorithm in terms of the efficiency and success ratio of APP. Therefore, hybrid path planning combining the three algorithms is helpful to improving the assembly path planning of complex products.

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Design and comparison of two evolutionary approaches for automated product design

Cited by 3 publications

References 35 publications

A Product Conceptual Design Method Based on Evolutionary Game

A Product Conceptual Design Method Based on Evolutionary Game

Hybrid hierarchical fuzzy group decision-making based on information axioms and BWM: Prototype design selection

Hybrid Assembly Path Planning for Complex Products by Reusing a Priori Data

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