Based on the distinct characteristic of the cigarette production process, the production planning and scheduling of the packing line is described as the multi-objective mixed-integer programming model to decide the se...
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ISBN:
(纸本)9783037858431
Based on the distinct characteristic of the cigarette production process, the production planning and scheduling of the packing line is described as the multi-objective mixed-integer programming model to decide the sequence and quantity of all the products, whose objective is not only to meet delivery date, but also to minimize all theprocessing costs and the transforming time in the process. The effectiveness of this model can be well verified in the scheduling decision support system for the production of the packing of real company.
In recent decades, analyzing and optimizing thermal systems have become of great interest to researchers. Recently, the engineers concentrated on variant concepts of artificial intelligence such as machine learning, s...
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In recent decades, analyzing and optimizing thermal systems have become of great interest to researchers. Recently, the engineers concentrated on variant concepts of artificial intelligence such as machine learning, simulation, fuzzy logic, game theory, and evolutionary computing to deal with complicated barriers and obstacles. Artificial intelligence and expert system techniques play an important role for surveying and controlling mechanical systems such as power plants and reservoirs. This is because of their interdisciplinary applications and versatile servicing potential in mathematical modeling of industrial systems. In this article, a new method called synchronous parallel shuffling self-organized Pareto strategy algorithm is presented which synthesizes different artificial techniques, nominally evolutionary computing, swarm intelligence techniques, and time adaptive self-organizing map that apply simultaneously incorporating with a stochastic data sharing behavior. Thereafter, it is applied to verify the optimum operating parameter of Damavand power plant as the biggest constructed power plant in Middle East with the potential of producing about 2300MW electricity sited in Tehran, capital of Iran, as a multi-objective, multi-modal complex problem. It is also proved that implementing the governing equations of power plant leads to a multi-objective problem where some of these objectives are non-linear, non-convex, and multi-modal with different type of real-life engineering constraints. The results confirm the acceptable performance of proposed technique in optimizing the operating parameters of Damavand power plant.
In this paper, we design a hybrid multi-objective algorithm using genetic and estimation of distribution based on design of Experiments At first, we apply orthogonal design and uniform design to generate an initial po...
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ISBN:
(纸本)9781424447541
In this paper, we design a hybrid multi-objective algorithm using genetic and estimation of distribution based on design of Experiments At first, we apply orthogonal design and uniform design to generate an initial population so that the population individual solutions scattered evenly in the feasible solutions space Second, we proposed a new convergence criterion to check whether the distribution of population has the obvious regularity When the population is convergence, we use the model-based method to reproduce new individual solutions, otherwise genetic operator was employed to generate offspring, The results of systematic experiments show that the hybrid algorithm this paper proposed capable of finding much better convergence near the Pareto-optimal solutions and better spread of solutions than RM-MEDA
Traffic congestion is the most crucial problem faced in the 21st century. To ease the severity of this problem, 'Road-Space Rationing' has been adopted by many countries. Carpooling service, also known as ride...
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ISBN:
(纸本)9781728113227
Traffic congestion is the most crucial problem faced in the 21st century. To ease the severity of this problem, 'Road-Space Rationing' has been adopted by many countries. Carpooling service, also known as ride-sharing, is a by-product of 'Road-Space Rationing' feature. With intelligent carpooling service, people can share rides more elegantly by maximizing the seat occupancy rate. In this paper, we introduce an efficient carpooling system that can provide the optimal route for a driver. To find the optimal route we use the Non-Dominated Genetic Sorting Algorithm (NSGA). In case of multiple near-optimal results, we figure out a single result by applying the proposed Crowding Distance Sorting Algorithm (CDSA). Finally, we show the comparison between each of the selected objectives and the optimal result. Our comparison shows that the optimal outcome has a minimum trade-off in respect of all individual objective best results.
This paper is concerned with the online order dispatching problem(OODP) of the recycling process of electronic products,whose aim is to allocate orders to vehicles properly while satisfying several practical *** this ...
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This paper is concerned with the online order dispatching problem(OODP) of the recycling process of electronic products,whose aim is to allocate orders to vehicles properly while satisfying several practical *** this paper,the customer satisfaction degree is first proposed as an objective of OODP,and then the considered OODP becomes a multi-objective OODP by optimizing the system cost and customer satisfaction degree *** taking the customer satisfaction into the objective design,a new model for the OODP of electronic products is *** order to tackle with the OODP with multiple optimization objectives,the Non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is *** experiment executed in this paper verifies the validity of multi-objective model in this paper and efficiency of the used algorithm NSGA-Ⅱ.
In this paper,we design a hybrid multi-objective algorithm using genetic and estimation of distribution based on design of *** first,we apply orthogonal design and uniform design to generate an initial population so t...
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In this paper,we design a hybrid multi-objective algorithm using genetic and estimation of distribution based on design of *** first,we apply orthogonal design and uniform design to generate an initial population so that the population individual solutions scattered evenly in the feasible solutions ***,we proposed a new convergence criterion to check whether the distribution of population has the obvious *** the population is convergence,we use the model-based method to reproduce new individual solutions,otherwise genetic operator was employed to generate *** results of systematic experiments show that the hybrid algorithm this paper proposed capable of finding much better convergence near the Pareto-optimal solutions and better spread of solutions than RM-MEDA.
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