• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.351-358
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• 2013

This paper proposes a multiobjective model describing the trade-offs involved in selecting the locations of drop-off boxes for collecting used products and transporting these products to designated locations. We assume the following reverse flow of used products. Owners of used products (cellular phones, digital cameras, ink cartridges, etc.) take them to the nearest drop-off box when the distance is reasonably short. We also assume that owners living closer to drop-off boxes dispose of more used products than do owners living farther from drop-off boxes. Different types of used products are collected, with each type requiring its own drop-off box. A transportation destination for each product is specified. Three objectives are considered: maximizing the volume of used products collected at drop-off boxes; minimizing the cost of transporting collected products to designated locations; and minimizing the cost of allocating space for drop-off boxes. We formulate the above model as a multiobjective integer programming problem and generate the corresponding set of Pareto optimal solutions. We apply the model to an area using population data for Chofu City, Tokyo, Japan, and analyze the trade-offs between the objectives.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.42-50
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• 2006

The multi-criteria group decision making (MCGDM) problem is to determine the best compromise solution in a set of competing alternatives that are evaluated under conflicting criteria by decision maker (DM)s. In this paper, we propose a mixed-integer programming (MIP) model to solve MCGDM. The existing method based on minimizing a distance measure such as Median Approach can not guarantee the best compromise solution because the element of median point vector is defined with respect to each criteria separately. However, by considering all criteria simultaneously, we generate median point that is better for locating the best compromise solution. We also utilize the concept of spatial dispersion index (SDI) to produce a threshold value, which is used as a guideline to choose either the Utopian Approach or the Median Approach. And we suggest using CBITP (Convex hull of individual maxima Based Interactive Tchebycheff Procedure) to provide DMs with various Pareto-optimal solutions so that DMs have broad range of selection.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.134-139
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• 2011

The problem of scheduling in permutation flowshops has been extensively investigated by many researchers. Recently, attempts are being made to consider more than one objective simultaneously and develop algorithms to obtain a set of Pareto-optimal solutions. Varadharajan et al. (2005) presented a multi-objective simulated-annealing algorithm (MOSA) for the problem of permutation-flowshop scheduling with the objectives of minimizing the makespan and the total flowtime of jobs. The MOSA uses two initial sequences obtained using heuristics, and seeks to obtain non-dominated solutions through the implementation of a probability function, which probabilistically selects the objective of minimizing either the makespan or the total flowtime of jobs. In this paper, the same problem of heuristically developing non-dominated sequences is considered. We propose an effective heuristics based on simulated annealing (SA), in which the weighted sum of the makespan and the total flowtime is used. The essences of the heuristics are in selecting the initial sequence, setting the weight and generating a solution in the search process. Using a benchmark problem provided by Taillard (1993), which was used in the MOSA, these conditions are extracted in a large-scale experiment. The non-dominated sets obtained from the existing algorithms and the proposed heuristics are compared. It was found that the proposed heuristics drastically improved the performance of finding the non-dominated frontier.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.1
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• pp.57-66
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• 2012

The paper deals with the development of a model for group decision making under multiple criteria. The Multi-criteria group decision making (MCGDM) is the process to determine the best compromise solution in a set of competing alternatives that are evaluated by decision makers having their own preferences on conflicting objectives. For MCGDM, we propose a Mixed-Integer Programming (MIP) model that implements a revised median approach by noticing that the original median approach cannot consider the willingness to reject and the indifferent preference conditions. The proposed MIP model tries to select a common best Pareto-optimal solution by maximizing the overall desirability considering the willingness to reject and the indifferent preference that represent the tolerance measure of each decision maker. To evaluate the effectiveness of the proposed model, we compared the results of the proposed model with those of the median approach. The results showed that the proposed MIP model produces more realistic and better compromised alternative by incorporating the decision maker's willingness to reject and the indifferent preferences over each criteria.

• Journal of Korean Association for Spatial Structures
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• v.8 no.1
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• pp.49-56
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• 2008

A multi-objective optimization approach is presented for force design of tensegrity structures. The geometry of the structure is given a priori. The design variables are the member forces, and the objective functions are the lowest eigenvalue of the tangent stiffness matrix that is to be maximized, and the deviation of the member forces from the target values that is to be minimized. The multi-objective programming problem is converted to a series of single-objective programming problems by using the constraint approach. A set of Pareto optimal solutions are generated for a tensegrity grid to demonstrate the validity of the proposed method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.734-745
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• 2021

In order to achieve a good and competitive FPSO design, the building cost and the motion performances are the two most critical and conflicting KPIs to be considered. In this study, the author's previous work (Lee, et al., 2021) on the optimization of an FPSO's hull dimensions with 1800 MBBLs storage capacity at Brazil field was extended using a multi-objective parametric optimization with the hull steel weight and the operability which are closely related to the building cost and the operational cost during the lifetime, respectively. For the purpose of more realistic and practical FPSO design, the constraints related to crew comfort and the safe helicopter take-off and landing operation were newly added. Also, the green water on deck was calculated accurately to check the suitability of the designed freeboard height using a newly developed real-time calculation module for the relative wave elevations. With aids of this updated optimization formulation, we presented multiple optimal FPSO dimensions expressed as a Pareto set which aids FPSO designers to conveniently select the practical and competitive dimensions. The excellence of the developed approach was verified by comparing the optimization results with those of FPSOs dimensioned for operation at West Africa and Brazil field.

• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.67-76
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• 2011

Order picking in automotive service parts warehouses is considered to be the most labor-intensive operation. Such warehouses contain hundreds of thousands of items, but normally 20% of products contribute to about 80% of turnover according to Pareto's 80-20 principle. Therefore most fast moving items are located near an outbound area which is called the "Golden Zone". Order picking routing efficiency is related to productivity and labor cost. However, most companies use simple methods. In this paper, we describe a series of computational experiments over a set of test cases where, we compared various previously existing routing heuristics to an optimal algorithm. We focus on examining the influence of the golden zone on the performance and selection of routing methods. The results obtained show that the optimal routing method increases the productivity at least 17.2%, and all the routing methods have better performance as the pick up rate from the golden zone increases.

• Smart Structures and Systems
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• v.14 no.1
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.893-904
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• 2013

In this paper, a Kriging metamodel-based multi-objective optimization strategy in conjunction with an NSGA-II(non-dominated sorted genetic algorithm-II) has been employed to optimize the valve-plate shape of the axial piston pump utilizing 3D CFD simulations. The optimization process for minimum pressure ripple and maximum pump efficiency is composed of two steps; (1) CFD simulation of the piston pump operation with various combination of six parameters selected based on the optimization principle, and (2) applying a multi-objective optimization approach based on the NSGA-II using the CFD data set to evaluate the Pareto front. Our exploration shows that we can choose an optimal trade-off solution combination to reach a target efficiency of the axial piston pump with minimum pressure ripple.

• Wind and Structures
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• v.29 no.5
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• pp.323-337
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• 2019

Wind tunnel testing technique has been established as a powerful experimental method for predicting wind-induced loads on high-rise buildings. Accurate assessment of the design wind load combinations for tall buildings on the basis of wind tunnel tests is an extremely important and complicated issue. The traditional design practice for determining wind load combinations relies partly on subjective judgments and lacks a systematic and reliable method of evaluating critical load cases. This paper presents a novel optimization-based framework for determining wind tunnel derived load cases for the structural design of wind sensitive tall buildings. The peak factor is used to predict the expected maximum resultant responses from the correlated three-dimensional wind loads measured at each wind angle. An optimized convex hull is further developed to serve as the design envelope in which the peak values of the resultant responses at any azimuth angle are enclosed to represent the critical wind load cases. Furthermore, the appropriate number of load cases used for design purposes can be predicted based on a set of Pareto solutions. One 30-story building example is used to illustrate the effectiveness and practical application of the proposed optimization-based technique for the evaluation of peak resultant wind-induced load cases.