An optimisation method for complex product design

Li, Ni; Yi, Wenqing; Bi, Zhuming; Kong, Haipeng; Gong, Guanghong

doi:10.1080/17517575.2012.743682

Cited by 28 publications

(9 citation statements)

References 34 publications

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“…Knowledge refers to the credible information, which has the potential to create value to an organization (Tomas and Hult, 2003). In new technology ventures, the ability to adapt and update knowledge is critical to innovation (Coombs and Hull (1998); Liao and Wu, 2010;Li, 2012;Li et al, 2013). Based on the RBV (Barney, 1991) and KBV (Kogut and Zander, 1992;Conner and Prahalad, 1996;Grant, 1996aGrant, , 1996b, knowledge includes technology knowledge, which refers to the businessrelevant knowledge about products, technologies and/or processes the new venture possesses (Burgers et al, 2008), and market knowledge, which describes the business-relevant knowledge about potential customers, distribution channels and how the market functions (Feng et al, 2003;Burgers et al, 2008).…”

Section: Knowledge Acquisition and New Product Developmentmentioning

confidence: 99%

Knowledge Management, Learning Behavior from Failure and New Product Development in New Technology Ventures

Chen

Nguyen

2014

Syst. Res.

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This research examines how knowledge management influences new product development (NPD) in new technology ventures. Researchers demonstrate that knowledge management is a critical antecedent of NPD. However, few studies have explored the role of knowledge management in NPD from a behavioral perspective. By employing experiential learning theory, this research develops a conceptual model to study the relationships between knowledge management, learning behavior arising from failures, and new ventures' NPD performance. Using a sample of 176 new high-tech technology ventures, the theoretical model is examined. The findings show that, for new technology ventures, knowledge acquisition facilitates NPD performance positively and that the relationship is partially mediated by learning behavior from failures. In addition, it is demonstrated that knowledge application plays a moderating role between learning behavior from failure and NPD. Both the theoretical contributions and practical implications are discussed.

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Section: Knowledge Acquisition and New Product Developmentmentioning

confidence: 99%

Knowledge Management, Learning Behavior from Failure and New Product Development in New Technology Ventures

Chen

Nguyen

2014

Syst. Res.

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“…A higher carrier frequency should be considered to minimize the impact of system noise on its accuracy. Several recently developed optimization methods may be used to optimize the entire system's design [13][14][15][16][17][18].…”

Section: Discussionmentioning

confidence: 99%

Novel Approach to Intersatellite Distance Measurement with High Accuracy

Wang

Zhou

2015

Journal of Guidance, Control, and Dynamics

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“…In the future, we plan to use fuzzy logic [41] to decide the most desired solution from Pareto solutions and study the multiobjective vehicle scheduling approach in the context of stochastic travel time with various methods [7], [52]- [55]. MengChu Zhou (S'88-M'90-SM'93-F'03) received the B.S.…”

Section: Discussionmentioning

confidence: 99%

Vehicle Scheduling of an Urban Bus Line via an Improved Multiobjective Genetic Algorithm

Zuo

Chen

Tan

et al. 2014

IEEE Trans. Intell. Transport. Syst.

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It is complex and difficult to perform the vehicle scheduling of urban bus lines, which is important to reduce the operational cost and improve the quality of public transportation services. One has to assign vehicles to cover a set of trips contained in a timetable while minimizing multiple objectives that may conflict with each other. Existing approaches combine these objectives in a weighted fashion to form a single objective and then use a single-objective optimization approach to solve it. However, they can only produce one solution, and it is not easy to assign a proper weight for each objective to obtain a superior solution that can balance different objectives. In this paper, a methodology is presented to create a set of Pareto solutions for this problem. First, a set of candidate vehicle blocks is generated. Then, multiple block subsets are selected from this candidate set by an improved multiobjective genetic algorithm combined with a departure-time adjustment procedure to obtain multiple Pareto solutions. To encode a solution, we propose a coding scheme that has a relatively short coding length and low decoding complexity. This approach is applied to a real-world vehicle scheduling problem of a bus line in Nanjing, China. Experiments show that this approach is able to quickly produce satisfactory Pareto solutions that outperform the actually used experience-based solution.

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An optimisation method for complex product design

Cited by 28 publications

References 34 publications

Knowledge Management, Learning Behavior from Failure and New Product Development in New Technology Ventures

Knowledge Management, Learning Behavior from Failure and New Product Development in New Technology Ventures

Novel Approach to Intersatellite Distance Measurement with High Accuracy

Vehicle Scheduling of an Urban Bus Line via an Improved Multiobjective Genetic Algorithm

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