• Management Science and Financial Engineering
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• v.10 no.1
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• pp.53-75
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• 2004

Most existing studies on time-dependent networks have been focused on finding a minimum delay path given a departure time at the origin. There, however, frequently happens a situation where users can select any departure time in a certain time interval and want to spend as little time as possible on traveling the networks. In that case. the delay spent on traveling networks depends on not only paths but also the actual departure time at the origin. In this paper, we propose a new problem in time-dependent networks whose objective is to find an optimal departure time given possible departure time interval at the origin. From the optimal departure time, we can obtain a path with minimum delay among all paths for possible departure times at the origin. In addition, we present an algorithm for finding an optimal departure time by enumerating trees which remain shortest path tree for a certain time interval.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.27-30
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• 1999

A spatio-temporal vector channel model is introduced for the position location (PL) estimation problem for CDMA cellular system environment. Two common ways for the PL make use of the AOA (Angle Of Arrival) and TDOA (Time Difference Of Arrival) from a subscriber to the multiple sensors (base stations). In this paper, we applied the derived vector channel to simulate the multipath channel for the angle of the signal arrival in CDMA systems. Cross-correlation method is a good candidate among other direction finding algorithms available in literature, especially in wideband modulation as in the CDMA system. The PL estimation errors are evaluated for different channels, which are obtained as a parameter of scattering radius of the suggested model. We noted that the number of sensors (base-stations) are related to the PL errors in favor of the available data.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.831-846
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• 2011

There are several methods, in the literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, a new method (based on fuzzy linear programming formulation) is proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems with a new representation of trapezoidal fuzzy numbers. The advantages of the proposed method over existing method are discussed. Also, it is shown that it is better to use the proposed representation of trapezoidal fuzzy numbers instead of existing representation of trapezoidal fuzzy numbers for finding the fuzzy optimal solution of fuzzy transportation problems. To illustrate the proposed method a fuzzy transportation problem (FTP) is solved by using the proposed method and the obtained results are discussed. The proposed method is easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.417-427
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• 2017

Power allocation is an important factor for cognitive radio networks to achieve higher communication capacity and faster equilibrium. This paper considers power allocation problem to each cognitive user to maximize capacity of the cognitive systems subject to the constraints on the total power of each cognitive user and the interference levels of the primary user. Since this power control problem can be formulated as a mixed-integer nonlinear programming (NP) equivalent to variational inequality (VI) problem in convex polyhedron which can be transformed into complementary problem (CP), we utilize modified projection method to solve this CP problem instead of finding NP solution and give a power control allocation algorithm with a subcarrier allocation scheme. Simulation results show that the proposed algorithm performs well and effectively reduces the system power consumption with almost maximum capacity while achieve Nash equilibrium.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.24-33
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• 2011

In this paper, we consider the Location-Routing Problem with simultaneous pickup and delivery (LRPSPD) which is a general case of the location-routing problem. The LRPSPD is defined as finding locations of the depots and designing vehicle routes in such a way that pickup and delivery demands of each customer must be performed with same vehicle and the overall cost is minimized. Since the LRPSPD is an NP-hard problem, we propose a hybrid heuristic approach based on genetic algorithms (GA) and simulated annealing (SA) to solve the problem. To evaluate the performance of the proposed approach, we conduct an experimental study and compare its results with those obtained by a branch-and-cut algorithm on a set of instances derived from the literature. Computational results indicate that the proposed hybrid algorithm is able to find optimal or very good quality solutions in a reasonable computation time.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.127-145
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• 2009

A novel approach is proposed to effectively estimate the quantile functions of normalized performance indices of reliability constraints in a reliability-based optimization (RBO) problem. These quantile functions are not only estimated as functions of exceedance probabilities but also as functions of the design variables of the target RBO problem. Once these quantile functions are obtained, all reliability constraints in the target RBO problem can be transformed into non-probabilistic ordinary ones, and the RBO problem can be solved as if it is an ordinary optimization problem. Two numerical examples are investigated to verify the proposed novel approach. The results show that the approach may be capable of finding approximate solutions that are close to the actual solution of the target RBO problem.

• Korean Journal of Computational Design and Engineering
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• v.4 no.3
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• pp.259-268
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• 1999

In order to reduce the cost of product and save the processing time, optimal nesting of two-dimensional part is an important application in number of industries like shipbuilding and garment making. There have been many studies on finding the optimal solution of two-dimensional nesting. The problem of two-dimensional nesting has a non-deterministic characteristic and there have been various attempts to solve the problem by reducing the size of problem rather than solving the problem as a whole. Heuristic method and linearlization are often used to find an optimal solution of the problem. In this paper, theoretical and practical nesting algorithm for rectangular, circular and irregular shape of two-dimensional parts is proposed. Both No-Fit-Polygon and Minkowski-Sum are used for solving the overlapping problem of two parts and the dynamic programming technique is used for reducing the number search spae in order to find an optimal solution. Also, nesting designer's expertise is complied into the proposed algorithm to supplement the heuristic method.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.117-129
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• 1999

We consider a Location-Allocation Problem with the Cost of Land(LAPCL). LAPCL has extremely huge size of problem and complex characteristic of location and allocation problem. Heuristics and decomposition approaches on simple Location-Allocation Problem were well developed in last three decades. Currently, genetic algorithm(GA) is used widely at combinatorics and NLP fields. A lot of research show that GA has efficiency for finding good solution. Our main motive of this research is developing of a GA in LAPCL. We found that LAPCL could be reduced to trivial problem, if locations were given. In this case, we can calculate fitness function by simple technique. We propose fourth alternative genetic algorithm. Computational experiments are carried out to find a best algorithm.

• Nonlinear Functional Analysis and Applications
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• v.26 no.3
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• pp.451-474
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• 2021

In this paper, we investigate a hybrid algorithm for finding zeros of the sum of maximal monotone operators and Lipschitz continuous monotone operators which is also a common fixed point problem for finite family of relatively quasi-nonexpansive mappings and split feasibility problem in uniformly convex real Banach spaces which are also uniformly smooth. The iterative algorithm employed in this paper is design in such a way that it does not require prior knowledge of operator norm. We prove a strong convergence result for approximating the solutions of the aforementioned problems and give applications of our main result to minimization problem and convexly constrained linear inverse problem.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.77-87
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• 2019

The Butterfly model, which aims to solve contradiction problems, defines the type of contradiction for given problems and finds the problem-solving objectives and their strategies. Unlike the ARIZ algorithm in TRIZ, the Butterfly model is based on logical proposition, which helps to reduce trial and errors and quickly narrows the problem space for solutions. However, it is hard for problem solvers to define the right propositional relations in the previous Butterfly algorithm. In this research, we propose a contradiction solving algorithm which determines the right problem-solving strategy just with yes or no simple questions. Also, we implement the Butterfly Chatbot based on the proposed algorithm that provides visual and auditory information at the same time and help people solve the contradiction problems. The Butterfly Chatbot can solve contradictions effectively in a short period of time by eliminating arbitrary alternative choices and reducing the problem space.