Tool-path airtime optimization problem during multi-contour processing in leather cutting is regarded as generalized traveling salesman problem. A hybrid intelligence algorithm is proposed. The improved genetic simulated annealing algorithm is applied to optimize cutting path selected arbitrarily firstly, and an optimal contour sequence is founded, then problem is changed into multi- segment map problem solved with dynamic programming algorithm. The algorithm's process and its various parameters are given simultaneously, and its performance is compared with simulated annealing and standard genetic algorithm alone. The results show that the algorithm is more effective.
Balancing convergence and diversity has become a key point especially in many-objective optimization where the large numbers of objectives pose many challenges to the evolutionary algorithms. In this paper, an opposition-based evolutionary algorithm with the adaptive clustering mechanism is proposed for solving the complex optimization problem. In particular, opposition-based learning is integrated in the proposed algorithm to initialize the solution, and the nondominated sorting scheme with a new adaptive clustering mechanism is adopted in the environmental selection phase to ensure both convergence and diversity. The proposed method is compared with other nine evolutionary algorithms on a number of test problems with up to fifteen objectives, which verify the best performance of the proposed algorithm. Also, the algorithm is applied to a variety of multiobjective engineering optimization problems. The experimental results have shown the competitiveness and effectiveness of our proposed algorithm in solving challenging real-world problems.
Double-workshop mixed chlor-alkali planned model production process is a multi-level multi-product multi-constraint mixed batch planning problem production line model, taking into account the actual production of joint production of dual-workshop mode of production to determine the products and materials at various workshops, various Plan period on the production quantity, at the end of each period to meet the delivery needs of the type and quantity simultaneously, during the product implementation plan the goal of profit maximization. It uses particle swarm algorithm to reach the answer, indicating the feasibility of the method and effectiveness through examples of the calculation.
With the development of science technology, the purchase in market aren’t just product itself. As a more effective way, industry product service system (IPS2) offers an integration of tangible product and intangible service to meet users’ need as much as possible with minimal resource, there is much achievement on IPS2 in academe. In this paper, the software rental service system for hardware enterprise the information-based manufacturing, the system consists of eight function modules with the platform of IBOS/ASP, and integrates resources of users (hardware enterprise), telecom operator, and third-part software developer to provide customized service.
Common platform design for product families is an important step in the modularity field. It is impossible to find the similar components in alterative design stages for the traditional similarity measure used in module division. So, a new common platform design method on extension-distance is presented. In different design environments, three distance concepts are discussed, namely, feature-to-feature, feature-to-set and set-to-set. The first concept will be employed as the base for extension-cluster method in the platform design on the thought of each structure’ s features between two adjacent structure components, while the second is used to build the tolerance-constraint function in the customized components division for the common platform generation. Last the adaptability measure is used to find the optimal case in the database. The method took the gasoline saw as an example.
A technical plan for realizing user toolkit for innovation (UTI) is proposed to release the vast creative energy of users, and help to make users qualified for the subject of innovation work. The model discussed in this paper is mainly aiming at two key problems in user innovation: 1) the essentials and technical access for the innovaiton style in the non-professional background of the ordinary users; 2) mechanism for driving innovaiton and optimization through user’s evaluation message. Interactive genetic algorithms (IGA) is applied to plan the functions of UTI, and is improved in several aspects for the demands of user innovation: 1) designed a selection based interactive evaluation method; 2) introduced market data as a kind of evaluation information; 3)built an integral user innovation decision making system; 4) visualized the optimizaion process, which enriched user’s perceptive interaction with UTI during working. The model also made regulations to IGA’s inner process, which strengthened IGA’s analyzing and mining ability to user’s evaluation information through latent local optimal chart making, solution space down-sizing and continuity building for discrete space.
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