Abstract
In the cloud manufacturing environment, innovative service composition is an important way to improve the capability and efficiency of resource integration and realize the upgrading and transformational upgrade of the manufacturing industry. In order to build a stable innovative service composition, we propose a novel composite model, which uses two-way selection according to their cooperation to recommend the most suitable partners. Firstly, a rough number is applied to quantify the semantic evaluation. Using the expectation of cooperative condition as reference points, prospect theory is then applied to calculate the cooperative desires for both sides based on participants’ psychological attitudes toward gains and losses. Next, the cooperative desires are used to establish the two-way selection model of innovative service composition. The solution is determined by using an improved teaching-learning-based optimization algorithm. Compared with traditional combined methods in the cloud manufacturing environment, the proposed model fully considers the long-neglected needs and interests of service providers. Prospect theory takes psychological expectations and varying attitudes of decision makers towards gains and losses into account. Moreover, an interval rough number is used to better preserve the uncertain information during semantic quantification. Experimental results verify the applicability and effectiveness of the proposed method.
Highlights
Since the formation of networking in the economic environment, competition for complementary advantages and optimized resources in the manufacturing industry exists between individual enterprises and between the supply chain and the industrial chain
Relying on the manufacturing resource-sharing service platform to integrate and optimize the allocation of advanced manufacturing technology and production modes, creating business values with the advantage of technological resources has become a standard practice in the manufacturing industry [1]
With the development and maturation of the Cloud manufacturing (CMfg) business model, numerous manufacturing resources have become available within the cloud manufacturing service platform, which provides more and greater opportunities for enterprises to innovate in-demand services and products quickly and
Summary
Since the formation of networking in the economic environment, competition for complementary advantages and optimized resources in the manufacturing industry exists between individual enterprises and between the supply chain and the industrial chain. With the development and maturation of the CMfg business model, numerous manufacturing resources have become available within the cloud manufacturing service platform, which provides more and greater opportunities for enterprises to innovate in-demand services and products quickly and . E aim of the research reported here is to improve the satisfaction levels for initiators and participants in service composition through the proposal of a novel selection model based on two-way selection. Eir proposed model introduces cooperative expectation in evaluation and recommend services by bilevel programming to make the selection result closer to the actual needs of both sides It only analyzes the process of solving a single service by linear regulation and does not study the composition service under mass data. It only analyzes the process of solving a single service by linear regulation and does not study the composition service under mass data. e abovementioned analysis shows that most studies mainly focus on how to select the best services, while less studies have taken demands as a reference for accurate evaluation and rarely considered the impact of decision maker’s psychological attitudes in the evaluation selection process
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