• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.217-225
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• 2009

Tone injection scheme has been known as one of peak to average power ratio (PAPR) reduction methods deployable to multi-carrier system like orthogonal frequency division multiplexing (OFDM). The basic idea in tone injection scheme is to enforce the constellation size larger so that each of original constellation points is mapped into the preassigned distinct locations. According to the tone injection scheme, it increases symbol power highly induced inherently by expanding constellation to get optimal PAPR reduction. In the other hand, to get optimal power increase, the PAPR would be reduced insufficiently with limited tone injection signal. To withstand these problems, this paper consider the reduction of the PAPR and power increase problem simultaneously, Toward this, the tone injection scheme accomplished by employing the weighted sum genetic algorithm which has been utilized to solve multi-objective optimization problem (MOOP). The simulation results verifies that the proposed scheme can control the effective PAPR performance and alleviation of power increase flexibly by the weight value at the expense of relatively low complexity.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.151-160
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• 2013

In the past decades, several algorithms based on evolutionary approaches have been proposed for solving job shop scheduling problems (JSP), which is well-known as one of the most difficult combinatorial optimization problems. Most of them have concentrated on finding optimal solutions of a single objective, i.e., makespan, or total weighted tardiness. However, real-world scheduling problems generally involve multiple objectives which must be considered simultaneously. This paper proposes an efficient particle swarm optimization based approach to find a Pareto front for multi-objective JSP. The objective is to simultaneously minimize makespan and total tardiness of jobs. The proposed algorithm employs an Elite group to store the updated non-dominated solutions found by the whole swarm and utilizes those solutions as the guidance for particle movement. A single swarm with a mixture of four groups of particles with different movement strategies is adopted to search for Pareto solutions. The performance of the proposed method is evaluated on a set of benchmark problems and compared with the results from the existing algorithms. The experimental results demonstrate that the proposed algorithm is capable of providing a set of diverse and high-quality non-dominated solutions.

• Wind and Structures
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• v.32 no.4
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• pp.355-369
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• 2021

Shape optimization of tall buildings is an efficient approach to mitigate wind-induced effects. Several studies have demonstrated the potential of shape modifications to improve the building's aerodynamic properties. On the other hand, it is well-known that the cross-section geometry has a direct impact in the floor area availability and subsequently in the building's profitability. Hence, it is of interest for the designers to find the balance between these two design criteria that may require contradictory design strategies. This study proposes a surrogate-based multi-objective optimization framework to tackle this design problem. Closed-form equations provided by the Eurocode are used to obtain the wind-induced responses for several wind directions, seeking to develop an industry-oriented approach. CFD-based surrogates emulate the aerodynamic response of the building cross-section, using as input parameters the cross-section geometry and the wind angle of attack. The definition of the building's modified plan shapes is done adopting the reduced basis approach, advancing the current strategies currently adopted in aerodynamic optimization of civil engineering structures. The multi-objective optimization problem is solved with both the classical weighted Sum Method and the Weighted Min-Max approach, which enables obtaining the complete Pareto front in both convex and non-convex regions. Two application examples are presented in this study to demonstrate the feasibility of the proposed strategy, which permits the identification of Pareto optima from which the designer can choose the most adequate design balancing profitability and occupant comfort.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.629-638
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• 2016

In this paper, we investigate an energy-efficient resource allocation problem in a two-way relay (TWR) network consisting of multiple user pairs and an amplify-and-forward (AF) relay. As the users and relay have individual energy efficiencies (EE), we formulate a multi-objective optimization problem (MOOP). A single-objective optimization problem (SOOP) of the MOOP is introduced using a weighted-sum method, which achieves a single Pareto optimal point of the MOOP. To derive the algorithm for the SOOP, we propose a more tractable equivalent problem using the Karush-Kuhn-Tucker conditions of the SOOP, which guarantees convergence at the local optimal points. The proposed equivalent problem can be efficiently solved by the proposed iterative algorithm. Numerical results demonstrate the effectiveness of the proposed algorithm in achieving the optimal EE in multi-user AF TWR networks.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.124-130
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• 2012

An injection mold cooling circuit for an automotive front bumper was optimally designed in order to simultaneously minimize the average of the standard deviations of the temperature and the difference in mean temperatures of the upper and lower molds for uniform cooling. The temperature distribution for a specified design was evaluated by Moldflow Insight 2010, a commercial injection molding analysis tool. For efficient design, PIAnO (Process Integration, Automation and Optimization), a commercial PIDO tool, was used to integrate and automate injection molding analysis procedure. The weighted-sum method was used to handle the multi-objective optimization problem and PQRSM, a function-based sequential approximate optimizer equipped in PIAnO, to handle numerically noisy responses with respect to the variation of design variables. The optimal average of the standard deviations and difference in mean temperatures were found to be reduced by 9.2% and 56.52%, respectively, compared to the initial ones.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.29-46
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• 2007

This paper makes an attempt to compare the two important methods for finding solutions of multi-item inventory problem with more than one conflicting objectives. Panda et al.[9] discusses a distance-based method to find the best possible compromise solution with variation of priority under the given weight structure. In this paper, the problem in [9] is revisited through the Pareto-optimal front of genetic algorithm with the help of a situation of retail stocking of FMCG business. The advantages of using the solutions from the perspective of the decision maker obtained through multi-objective optimization are highlighted in terms of population search, weighted goals and priority structure, cost, set of compromise solutions along with prevention of stock-out situation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.3
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• pp.26-38
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• 2020

Mixture design of self-compacting concrete is a typical multi-criteria decision making problem and conventional mixture designs are based on the low level engineering method like trials and errors through iteration method to satisfy the various requirements. This study concerns with performing the straightforward multiobjective design optimization of economic SCC mixture considering relative importances of the various requirements and cost-effectives of SCC. Total five requirements of 28day compressive strength, filling ability, segregation stability, material cost and mass were taken into consideration to prepare the objective function to be formulated in form of the weighted-multiobjective mixture design optimization problem. Economic SCC mixture computational design can be given in a rational way which considering material costs and the relative importances of the requiremets and from the result of this study it is expected that the development of SCC mixtue computational design and the consequent univeral concrete material design optimization methodology can be advanced.

• International Journal of Reliability and Applications
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• v.15 no.1
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• pp.23-50
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• 2014

This paper deals with formulation of optimum multi-objective modified step-stress accelerated life test (ALT) plan for Burr type-XII distribution under type-I censoring. Since it is impractical to estimate only one objective parameter after conducting costly ALT tests; also, it is not desirable to assume instantaneous changes in stress levels because of limited capacity of test equipments and the presence of undesirable failure modes, therefore, an optimum multi-objective modified step-stress ALT plan has been designed. The optimal test plan consists in determining the optimum low stress level and optimal time at which stress starts linearly increasing from low stress by minimizing the weighted sum of the asymptotic variances of the maximum likelihood estimator of quantile lifetimes at design constant stress. The method developed has been illustrated using an example. Sensitivity analysis has been carried out. Comparative study has also been done to highlight the merits of the proposed model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.2
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• pp.114-126
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• 2009

In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.611-622
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• 2021

Composite material-due to low density-causes weight savings, which results in lower fuel consumption of transport vehicles. The aim of the research was to change the existing base-plate of the aluminum airplane container with the composite sandwich plate in order to reduce the weight of the containers of cargo aircrafts. The newly constructed sandwich plate consists of aluminum honeycomb core and composite face-sheets. The face-sheets consist of glass or carbon or hybrid fiber layers. The orientations of the fibers in the face-sheets were 0°, 90° and ±45°. Multi-objective optimization method was elaborated for the newly constructed sandwich plates. Based on the design aim, the importance of the objective functions (weight and cost of sandwich plates) was the same (50%). During the optimization nine design constraints were considered: stiffness, deflection, facing stress, core shear stress, skin stress, plate buckling, shear crimping, skin wrinkling, intracell buckling. The design variables were core thickness and number of layers of the face-sheets. During the optimization both the Weighted Normalized Method of the Excel Solver and the Genetic Algorithm Solver of Matlab software were applied. The mechanical properties of composite face-sheets were calculated by Laminator software according to the Classical Lamination Plate Theory and Tsai-Hill failure criteria. The main added-value of the study is that the multi-objective optimization method was elaborated for the newly constructed sandwich structures. It was confirmed that the optimal new composite sandwich construction-due to weight savings and lower fuel consumption of cargo aircrafts - is more advantageous than conventional all-aluminum container.