Owing to the extensive applications of the smart home system in the family level, the optimization design for the smart home system has received considerable research attention. In this paper, based on the practical c...
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Owing to the extensive applications of the smart home system in the family level, the optimization design for the smart home system has received considerable research attention. In this paper, based on the practical commercial operation, the fuzzy programming model and its application are studied for the optimization design problem of the smart home system. A fuzzy multi-objective evaluation model is first proposed for the optimization design scheme. Then, the optimization design scheme and the optimization production programming are investigated based on the fuzzy set theory. Finally, the fuzzy programming model of the optimization design of the smart home system and its application are discussed.
Due to long lead times, uncertain outcomes and lack of enough historical data, pharmaceutical research and development (R &D) portfolio selection is a often very complex decision issue. The aim of this paper is to...
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Due to long lead times, uncertain outcomes and lack of enough historical data, pharmaceutical research and development (R &D) portfolio selection is a often very complex decision issue. The aim of this paper is to investigate pharmaceutical R &D portfolio selection with unavailable and unreliable project information, where the borrowed capital is allowed. Based on fuzzy set theory, we propose a pharmaceutical R &D portfolio optimization model with minimum borrowed capital by taking into account corporate strategy in developing new products, scarcity of resources, lack of investment budget and cardinality constraint. In the proposed model, the pharmaceutical R &D company is assumed to achieve the objectives of maximizing terminal wealth and minimizing the cumulative borrowed capital over the whole investment horizon. Then, we transform the proposed bi-objective model into the corresponding single-objective model by using the weighted sum approach and employ the modified artificial bee colony (MABC) algorithm to solve the transformed model. Finally, we provide a numerical example to illustrate the application of our model.
In this paper, we introduce two different kinds of iterative algorithms, which are based on the inertial Tseng's method and the viscosity method. They are intended to solve the variational inequality problems gove...
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In this paper, we introduce two different kinds of iterative algorithms, which are based on the inertial Tseng's method and the viscosity method. They are intended to solve the variational inequality problems governed by the mappings of pseudo-monotone type. Strong convergence theorems are established in Hilbert spaces. Practical examples in fuzzy environment are given to show the applicability and effectiveness of the proposed algorithms.
As the increasing trend of global consumption of waste electrical and electronic equipment (WEEE), the recycling of WEEE has been thought highly of. In order to solve the problems of high economic cost, environmental ...
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As the increasing trend of global consumption of waste electrical and electronic equipment (WEEE), the recycling of WEEE has been thought highly of. In order to solve the problems of high economic cost, environmental detrimental caused by improper recycling, ignorance of social benefits of recycling, uncertain recycling amount and single recycling channel in recycling process of WEEE, this paper proposes a sustainable multi-objective WEEE double recycling channel fuzzy programming model based on triple bottom line (TBL) theory. First of all, TBL is used to develop sustainable multi-objective recycling models concerning economy, environment and society. Secondly, the model is fuzzed. This process includes two steps: the first step is to take WEEE recycling quantity as a triangular fuzzy parameter, and use fuzzy chance constraint method to transform fuzzy constraint into an equivalent clear condition;the second step is to fuzzify suboptimal objective in the model by defining objective membership degree, and transform multi-objective optimization problem into a single-objective optimization problem based on the maximum satisfaction. Finally, taking a recycling enterprise in Shantou, China, as an example, genetic algorithm (GA) and particle swarm optimization (PSO) are comparatively used to solve a calculation case related to the model and the contribution of the model is verified by comparing economic cost, environmental impact and social benefits of the dual recycling channels.
In this study, a freight routing problem considering both soft delivery time windows and demand and capacity uncertainty in a road-rail intermodal transportation system is investigated. According to fuzzy set theory, ...
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In this study, a freight routing problem considering both soft delivery time windows and demand and capacity uncertainty in a road-rail intermodal transportation system is investigated. According to fuzzy set theory, uncertain demands and capacities are formulated as trapezoidal fuzzy numbers. Soft delivery time windows under a fuzzy environment is established, in which fuzzy periods caused by early and late deliveries that lead to penalty are modeled based on maximum functions. To solve the routing problem yielding the above characteristics, this study designs a fuzzy mixed-integer nonlinear programmingmodel whose objective is to minimize the total costs created in the road-rail intermodal transportation activities. After using the fuzzy expected value method to address the fuzzy objective, two fuzzy approaches, i.e., fuzzy chance-constrained programming method and fuzzy ranking method, are separately adopted to undertake the defuzzification of the fuzzy constraints. Improved linear formulations of the model are then produced to make it easier to solve. A simulation-based reliability modeling is developed to quantify the reliability of the optimization results given by different fuzzy approaches under different parameter settings in a simulation environment. Finally, an empirical case is presented to verify the feasibility of the proposed methods. The effects of demand and capacity fuzziness on the routing optimization are revealed, and an optimization procedure that helps decision-makers to select a more suitable fuzzy approach and determine the best parameter setting for a given case is demonstrated. Some insights that are helpful for organizing a reliable transportation are also drawn.
The problem of project portfolio selection consists in allocating resources (for instance money) to a set of proposals optimizing certain impact measures [Litvinchev et al. (J Comput Syst Sci Int 50(6):942-952, 2011)]...
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The problem of project portfolio selection consists in allocating resources (for instance money) to a set of proposals optimizing certain impact measures [Litvinchev et al. (J Comput Syst Sci Int 50(6):942-952, 2011)]. We develop a model that takes into account the following characteristics: projects tasks;different resources allocation policies;interdependence between tasks and/or projects;portfolio balancing rules;uncertainty in the overall budget;and uncertainty in the amount of resources requested by tasks. Uncertain parameters are represented as fuzzy triangular numbers and fuzzyprogramming is employed for solving the model with uncertainty. Computational results are presented for medium and large scale instances.
This paper considers the shortest path problem with fuzzy arc lengths. According to different decision criteria, the concepts of expected shortest path, a-shortest path and the most shortest path in fuzzy environment ...
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This paper considers the shortest path problem with fuzzy arc lengths. According to different decision criteria, the concepts of expected shortest path, a-shortest path and the most shortest path in fuzzy environment are originally proposed, and three types of models are formulated. In order to solve these models, a hybrid intelligent algorithm integrating simulation and genetic algorithm is provided and some numerous examples are given to illustrate its effectiveness. (c) 2005 Elsevier Inc. All rights reserved.
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