In recent years, flash evaporation processes have received an increased attention in the wine industry for must concentration applications. Specific constraints related to the wine industry area had lead to many impro...
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In recent years, flash evaporation processes have received an increased attention in the wine industry for must concentration applications. Specific constraints related to the wine industry area had lead to many improvements of flash evaporators initially designed for seawater desalination. In particular the quality of the vintage, the transportability of the system and the environmental impact are of main interest. Moreover, the preliminary design of such systems must also consider robustness criteria. Obviously, variations of temperatures and flow rates of liquids at the inlet of the process can dramatically impact the quality of the product at the system outlet. In particular, deviations from the target values of temperature and alcoholic volume fraction can lead to a severe degradation of the vintage. As it is common in product design to have multiple performance measures, the robust design problem is addressed using a multi-objective approach. A trade-offs is introduced between two main design objectives: (i) the improvement in overall performance (product quality, transportability, environmental impact and costs) and (ii) the lowering of the sensitivity of the product quality under uncertainty. These main objectives are related to several elementary objectives corresponding to design criteria and a preference aggregation method is used to formulate the two different design objectives. Objectives are linked to weighting parameters values equivalent to priority levels. The selection of the most preferred design solution is discussed according to different trade-off strategies. The generation of the Pareto set is addressed by the non dominated sorting genetic algorithm NGSAII. From computing results, our recommendations concern the compromise between performance and robustness of flash evaporators. In this context, the final alcoholic volume fraction of the wine is the most sensitive parameter, which justify to maintain a high value of evaporative capacity when d
Cross-docking is a material handling and distribution technique in which products are transferred directly from the receiving dock to the shipping dock, reducing the need for a warehouse or distribution center. This p...
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Cross-docking is a material handling and distribution technique in which products are transferred directly from the receiving dock to the shipping dock, reducing the need for a warehouse or distribution center. This process minimizes the storage and order-picking functions in a warehouse. In this paper, we consider cross-docking in a supply chain and propose a multi-objective mathematical model for minimizing the make-span, transportation cost and the number of truck trips in the supply chain. The proposed model allows a truck to travel from a supplier to the cross-dock facility and from the supplier directly to the customers. We propose two meta-heuristic algorithms, the non-dominatedsortinggeneticalgorithm (NSGA-II) and the multi-objective particle swarm optimization (MOPSO), to solve the multi-objective mathematical model. We demonstrate the applicability of the proposed method and exhibit the efficacy of the procedure with a numerical example. The numerical results show the relative superiority of the NSGA-II method over the MOPSO method. (C) 2015 Elsevier B.V. All rights reserved.
In a stub network which is connected to Internet via more than one edge routers to Internet Service Providers, the users are classified into groups where each group is connected to one edge router. Each edge link of t...
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ISBN:
(纸本)9781479922741;9781479922758
In a stub network which is connected to Internet via more than one edge routers to Internet Service Providers, the users are classified into groups where each group is connected to one edge router. Each edge link of the stub network has its own maximum available bandwidth provided by the ISP. If the group of users assigned to an edge link downloads a total inbound traffic which exceeds the maximum available bandwidth provided by that edge link, then the link is said to be over-utilized. On the contrary some group of users might download very less, under utilizing the capacity of the edge link assigned to them. In this paper, we try to provide a suitable solution for this problem by finding a better possible way of assignment of users to edge links so that the inbound traffic of all the edge links is fairly load balanced and no link is over or under utilized. This problem is framed as a multi-objective optimization problem with three objectives - load balance the inbound traffic, minimize user movements and minimize the intradomain cost. We improve on an earlier approach [1] using NSGA II [2] to minimize the first two objectives and implement third objective. Our results show that our approach load balances the inbound traffic as well as minimizes the user movements and also show that intra domain cost affects other two objectives.(1)
Aiming at the limitation of flexible job shop scheduling (JSP), a multi-objective optimization model of JSP is constructed, which takes the maximum completion time and delivery time as the objective function. Consider...
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ISBN:
(数字)9781728182889
ISBN:
(纸本)9781728182896
Aiming at the limitation of flexible job shop scheduling (JSP), a multi-objective optimization model of JSP is constructed, which takes the maximum completion time and delivery time as the objective function. Considering the actual inventory size of job shop, a nondominatedgeneticalgorithm is proposed. Combined with the actual inventory and demand, the program is developed to verify the feasibility and effectiveness of the algorithm. The results show that the algorithm can meet the delivery time and the maximum completion time at the same time, considering the size of inventory and achieve satisfactory results.
The development of an efficient separation and purification process for ternary aqueous azeotropes is very important to balance their economic and environmental benefits. Based on the high efficiency of extractive dis...
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The development of an efficient separation and purification process for ternary aqueous azeotropes is very important to balance their economic and environmental benefits. Based on the high efficiency of extractive distillation in azeotrope separation and the low consumption of pervaporation technology, it is essential to study the feasibility of the coupling process and its advantages when compared with the single distillation process. Considering a tetrahydrofuran/toluene/water azeotropic system, suitable extractants for the process of extracting and rectifying azeotropes were selected by analyzing the phase equilibrium and intermolecular interaction bonding mechanism. Implementing the non-dominatedsortinggeneticalgorithm with economic cost and gas emissions (CO2, SO2 and NOx) as the multi-objective for process optimization, the optimal parameters and process scheme of extractive distillation and coupling process were obtained. In addition, different azeotrope feed compositions were analyzed to further judge the separation effect of the coupling process. Based on the multi-objective optimization algorithm, it was found that the coupled process was better than the single extractive distillation process economically and environmentally, which has significance for the separation of ternary aqueous azeotropes.
The most significant factor for the survival of an enterprise under a high level of competition is new product development (NPD). As a result, selecting a potential NPD project portfolio to gain competitive advantage ...
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The most significant factor for the survival of an enterprise under a high level of competition is new product development (NPD). As a result, selecting a potential NPD project portfolio to gain competitive advantage has become a major concern to enterprises. However, selection of an NPD project portfolio is intricate due to multiple selection criteria and factors. This study focuses on optimizing an NPD project portfolio selection problem. To this end, Balance Score Card (BSC) is employed as a comprehensive framework to define NPD project selection criteria. Afterward, a multi-objective mathematical model is formulated that attempts to maximize total outcome, to minimize total risk, and to maximize strategic advantages. Our proposed model also takes into account suppliers, consumer demands, and project interdependencies. Because of the NP-hardness of the proposed model, two multi-objective metaheuristic algorithms, multi-objective particle swarm optimization (MOPSO), and non dominated sorting genetic algorithm (NSGA-II) are applied to solve the proposed model. It should be noted that the performance of algorithms is evaluated using the epsilon-constraint method and enhanced using response surface methodology (RSM). Finally, several numerical examples of different sizes are generated to compare the performance of metaheuristic solution methods based on four comparing metrics. Computational results show that NSGA-II outperforms MOPSO in terms of all the evaluation metrics. (C) 2020 Elsevier Ltd. All rights reserved.
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