With the number of alternative systems increasing, the system portfolio selection problem for large-scale complex systems is an non-deterministic polynomial (NP)-hard problem. The time cost of the classification selec...
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With the number of alternative systems increasing, the system portfolio selection problem for large-scale complex systems is an non-deterministic polynomial (NP)-hard problem. The time cost of the classification selection algorithm used for the portfolio selection is intolerable;thus, improving the algorithm is necessary. In this paper, first, the weapon system portfolio selection (WSPS) model is categorized into two types: single objective and multiobjective;the optimization difficulties are analyzed;and the feasible solution space reduction strategy is given. Second, a portfolio selection optimization algorithm based on the difference evolution technique for order preference by similarity to ideal solution (DE-TOPSIS) is proposed where the weapon system weighting method TOPSIS is integrated with the DE algorithm. Finally, considering different weapon system scales, the advantages of the proposed algorithm are illustrated by comparing it with two other algorithms in a single-target case and two other algorithms in a multiobjective case. The results indicate that the DE algorithm always has better performance with regard to optimal solution quality, convergence speed, and algorithm stability.
For complex equipment, designers are challenged to reduce the expense while satisfying high requirements of system reliability. This article focuses on the multiobjective reliability-redundancy allocation problem for ...
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For complex equipment, designers are challenged to reduce the expense while satisfying high requirements of system reliability. This article focuses on the multiobjective reliability-redundancy allocation problem for serial parallel-series systems to balance the conflicts between system reliability and design cost. The multiobjective reliability-redundancy allocation problem model for serial parallel-series systems is established with constraints on system reliability and design cost. An importance measure-based and harmony search-based multiobjective particle swarm optimization algorithm is proposed to solve the multiobjective model effectively based on the importance measure-based harmony search and multiobjective particle swarm optimization algorithm. The performance of the importance measure-based and harmony search-based multiobjective particle swarm optimization algorithm is verified by comparison with the nondominated sorting genetic algorithm and importance measure-based multiobjective particle swarm optimization algorithm. In Experiment 1, the performance of the importance measure-based and harmony search-based multiobjective particle swarm optimization algorithm is better than that of the nondominated sorting genetic algorithm and importance measure-based multiobjective particle swarm optimization, and the importance measure-based and harmony search-based multiobjective particle swarm optimization algorithm also can get the Pareto front with better uniformity. Compared to the nondominated sorting genetic algorithm, four cases with different constraints of system reliability and design cost are considered in Experiment 2, and the importance measure-based and harmony search-based multiobjective particle swarm optimization algorithm applies to the systems with the lower system reliability constraints and the higher design cost constraints.
This paper presents the solution procedure of multiobjective nonlinear transportation problem (MNOTP) where the cost coefficients of the objective functions, and the supply and the unknown demand parameters have been ...
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This paper presents the solution procedure of multiobjective nonlinear transportation problem (MNOTP) where the cost coefficients of the objective functions, and the supply and the unknown demand parameters have been formulated as interval numbers by the decision maker. This problem has been converted into a conventional MNOTP where to minimize the interval nonlinear objective functions, the order relations that define the choice between intervals have been determined by the interval arithmetic. Also, the constraints with interval supply and unknown demand parameters have been transformed into its deterministic forms. Then the deterministic problems have been solved by two compromise programming methods. Finally, a numerical example is presented to illustrate the efficiency of the proposed procedure as well.
Comprehensive quality evaluation is the measure of the members' comprehensive ability and the premise and foundation of improving the team's operation efficiency. How to accurately obtain the comprehensive qua...
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ISBN:
(纸本)9781728128160
Comprehensive quality evaluation is the measure of the members' comprehensive ability and the premise and foundation of improving the team's operation efficiency. How to accurately obtain the comprehensive quality of members has been a widely concerned issue in the academic and application fields. Taking cooperative performance as the main observation index, this paper proposes a comprehensive quality evaluation model based on cooperative performance, and analyzes the characteristics and shortcomings of this model. In order to solve the problem that the solution cannot be guaranteed, the method of multi objective programming is applied to give the solution strategy based on the deviation variable. Finally, the feasibility and effectiveness of the model are analyzed with a case study. Theoretical analysis and example calculation show that the model has good interpretability and operability, which not only improves the existing evaluation methods to a certain extent, but also has wide application value in the fields of resource allocation, artificial intelligence and recommendation system.
This paper presents a fuzzy goal programming procedure to solve multiobjective quadratic bilevel programming problems, where all the parameters involved in objectives of each level decision maker and in system constra...
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ISBN:
(纸本)9781467357869
This paper presents a fuzzy goal programming procedure to solve multiobjective quadratic bilevel programming problems, where all the parameters involved in objectives of each level decision maker and in system constraints are fuzzily defined. In model formulation process the fuzzy numbers associated with the parameters are described by using the concept of α-cut of fuzzy numbers. Then the model is decomposed on the basis of the tolerance limits of fuzzy numbers. Individual decision at each objective at each level is found in isolation to find the fuzzy goals of the objectives. Then a fuzzy goal programming model is developed to minimize the group regret of degree of satisfactions of both the decision makers and to achieve the highest degree (unity) of each of the membership goals for overall benefit of the organization. In the decision process Taylor's series linear approximation technique is applied to make the quadratic membership goals to its equivalent linear form. To establish the efficiency of the proposed approach a numerical example is solved.
In this paper, we consider a nonsmooth multiobjective semi-infinite mathematical programming problems with equilibrium constraints (MOSIMPECs). We introduce the concept of Mordukhovich stationary point for the nonsmoo...
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In this paper, we consider a nonsmooth multiobjective semi-infinite mathematical programming problems with equilibrium constraints (MOSIMPECs). We introduce the concept of Mordukhovich stationary point for the nonsmooth multiobjective semi-infinite mathematical programming problems with equilibrium constraints in terms of the Clarke subdifferentials. Further, we establish that the M-stationary conditions introduced in this paper are strong KKT type sufficient optimality conditions for the nonsmooth multiobjective semi-infinite mathematical programming problems with equilibrium constraints under generalized invexity assumptions. We also illustrate our result with an example. (C) 2016 Published by Elsevier B.V.
In this paper, a multiobjective portfolio selection model is studied, wherein all parameters like return, risk, etc., as well as decision variables are varying in intervals. A methodology is developed using interval a...
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In this paper, a multiobjective portfolio selection model is studied, wherein all parameters like return, risk, etc., as well as decision variables are varying in intervals. A methodology is developed using interval analysis to derive an acceptable efficient portfolio. The theoretical developments are justified by assigning the degree of acceptability to every feasible portfolio as well as assigning goals to each objective function. This theoretical development is illustrated in a portfolio selection model with data from Bombay Stock Exchange, India, which justifies that the results obtained by the proposed method are close enough to the existing result.
A worker assignment job rotation problem with the heterogeneous workers and the jobs with different workload level is presented in this paper. Both productivity and ergonomic criteria are considered in the problem and...
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Background: Usual guidelines recommend symmetric load carriage over asymmetric load carriage. Whether this recommendation is valid for subjects with asymmetric body alignment, such as those with scoliosis, remains unc...
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Background: Usual guidelines recommend symmetric load carriage over asymmetric load carriage. Whether this recommendation is valid for subjects with asymmetric body alignment, such as those with scoliosis, remains unclear. Scoliosis is both a subject-dependent and time-variant condition. Interventions are generally employed to prevent the abnormal spinal curvature from progressing. Objectives: To investigate the effects of an asymmetric load carriage on lateral spinal deformity in participant with scoliosis. Study design: Repeated measure and single-case experimental designs Methods: Photogrammetry was employed to measure the scoliotic curvature changes in thoracic and lumbar regions without a load (0%) and with a single-strap cross-chest bag loaded at 2.5%, 5%, 7.5%, 10% and 12.5% of body weight. Statistical tests and programming models were adopted to determine the loading conditions (placement and weight of the bag) with optimal and minimal corrections of the affected and unaffected scoliotic spinal regions, respectively. Results: Significant short-term postural correction of scoliosis was achieved through applying an asymmetric load on the ipsilateral shoulder relative to the apex location of the major scoliotic curve. Conclusion: A subject-specific optimal loading configuration was determined using a programming model. The results suggest that the application of a properly controlled asymmetric load carriage might be possible for reducing scoliotic spinal curvature. Further study of the long-term effects of subject-specific optimal asymmetric load carriage on scoliotic spinal curvatures is warranted. Clinical relevance Short-term reduction of scoliotic spinal curvatures under asymmetric load carriage was demonstrated. Thoracic curvatures could be reduced when asymmetric loading was applied on the ipsilateral shoulder relative to the scoliotic apex. multiobjective programming was applied to determine the optimal weight of asymmetric load for participant with sco
Based on the credibility theory,this paper is devoted to the fuzzy multiobjective programming *** this purpose, we first present the expected value model of the fuzzy multiobjective programming problem and investigate...
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Based on the credibility theory,this paper is devoted to the fuzzy multiobjective programming *** this purpose, we first present the expected value model of the fuzzy multiobjective programming problem and investigate its properties. To solve the problem,we design a theoretical method under the credibility measure,called the method of primary objective function,which transforms the multiobjective problem into the single objective ***,a numerical example is given to explain the method of primary objective function specifically. The theoretical results obtained in this paper can facilitate us to design algorithms to solve the FMOP problem.
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