Abstract
In a collaborative product design project, reasonable resource allocation can shorten the development cycle and reduce cost. Team capacity evaluation and a task-team scheduling model are presented. A collaborative team capacity model is constructed, and a 2-tuple linguistic method is used to evaluate the capacity of collaborative teams. Next, the matching degree between design task and collaborative team is defined. A collaborative product design scheduling model considering task-team matching is developed. Combined with the simulated annealing operator, based on the single-coding strategy, self-adaptive multi-point cross and mutation, an improved genetic algorithm is proposed to solve the model. Finally, a case study is presented to validate the method.
Highlights
With the increasing global competition and growing complexity of products, the division of labour is becoming increasingly specialized
Through cross-organizational collaborative product design, it can realize the maximization of resource integration and knowledge sharing as well as the improvement of design efficiency
There is a great amount of research work on the task and resource allocation of a collaborative design project
Summary
With the increasing global competition and growing complexity of products, the division of labour is becoming increasingly specialized. ; l0uÞ according to the improved EOWA operator, and aggregate the integrated information ð~syij; a~yijÞ according to Eq (5) to obtain the comprehensive evaluation information of team j for task i in capacity y, denoted as (syij, ayij). A higher matching degree ensures that the team can accomplish the tasks high-efficiency and high-quality, but it means higher cost To address this trade-off, this paper constructs a task-team matching degree model of collaborative product design project. The matching degree calculation model between project task i and collaborative team j at the dimension of available resource, denoted as TRij, is defined as follows: TRij. Ã girj eri ð8Þ where r denotes the rth resource, bri is the weight of the rth resource for taski, girj is the available amount of the rth resource of team j for task i, and eri is the required amount of the rth resource for task i. The probability (pi) that can be selected is set as follows: pi
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