• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.73-80
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• 1986

This paper deals with the problem of the optimal location of warehouses in the two stage distribution system, i.e., the distribution system where the product is transported from plants to customer areas via warehouses. The Problem is formulated with a zero-one mixed integer programming and an efficient branch and bound algorithm is then used to solve the problem. In order to obtain the solution of this problem, this paper shows the procedure of conversion of two stage distribution system into one stage distribution system. An improved method of solving the linear programming at the nodes and branching decision rule is also showed by this study.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.8
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• pp.753-757
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• 2008

In this paper, we propose a new scheduling strategy for dynamic programming in Grid environment. The key idea of this scheme is to reduce the execution time of a job by dividing the dynamic table based on the locality of table and allocating jobs to nodes which minimize network latency. This scheme obtains optimal concurrency by constructing the dynamic table using a distributed top down method. Through simulation, we show that the proposed Grid strategy improves the performance of Grid environment compared to previous branch-bound strategies.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.1
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• pp.58-65
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• 2002

When we estimate the optimal solution satisfy the objective function and subjective equation in the integer programming, The optimal solution of the objective function Z is decided by the positive integer at extreme point or revised extreme point in the convex set. The convex set is made up the linear subjective equation. The purpose of the paper is thus to establish a stepwise optimization in the integer programming model by estimating the variation △C/sub j/ of the constant term C/sub j/ in the linear objective function, after an application of the modified Branch & Bound method.

• Proceedings of the KIEE Conference
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• 1985.07a
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• pp.111-114
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• 1985

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1780-1783
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• 2002

A problem of signal transmitted and received in OFDM systems is considered. In particular, an efficient solution to the problem of blind channel estimation based on Maximum Likelihood (ML) principle has been investigated. The paper proposes a new upper-bound cost, used in conjunction with a standard branch and bound integer programming technique for solving the ML problem. The tighter upper-bound cost exploits a finite-alphabet property of the transmitted signal. The proposed upper-bound cost was found to greatly speed up the ML algorithm, thus reducing computational complexity. Experimental results and discussion are included.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.12-21
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• 2010

Recently, "Service of information perspective" that is an important issue is that a company searches customers that interested in certain information and the company offers information to the customers. This service can gain high effects by low cost because of supporting selective information. In most recently, Reverse Skyline using Skyline Approximation(RSSA) is proposed to process services of information provider's perspective. RSSA has problem to defects about waste of processing time and memory. In this paper, Efficient Reverse Skyline(ERSL) Algorithm is proposed for Efficient processing the Skyline. ERSL is new Algorithm using Branch and Bound Skyline(BBS) reduces the waste of processing time and memory. When we execute the variety experimentation to valuation ERSL algorithm's capacity. It is proved the best efficient algorithm among the others because ERSL is flexibly kept the established capacity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.12
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• pp.2386-2396
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• 1994

In this paper, an optimal algorithm for the design of 1-D FIR filters with finite precision coefficients is proposed. The algorithm is based on the observation that the frequency constraints of a sub-problems(SP) in the branch and bound algorithm, which repeatedly use LP(linear programming), are closely related with those of neighboring SPs. By using the relationship between the SPs, the proposed algorithm reduces the number of constraints required for solving each SP with Lp, whereas the conventional algorithm employs all the constraints, which are required for solving the initial problem. Thus, the overall computational load for the design of FIR filters with finite precision coefficients is significantly alleviated, compared to the conventional branch and bound algorithm. Also, a new branching scheme for the design of FIR filters with sum-of-power-of-two(SOPOT) coefficients is proposed. It is shown that the computational load for the design fo SOPT coefficient filters can be further reduced with the new branching scheme.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.4
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• pp.361-371
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• 2012

In order to improve the efficiency of the branch-and-bound method for mixed-discrete nonlinear programming, a nonuniform convergence tolerance scheme is proposed for the continuous subproblem optimizations. The suggested scheme assigns the convergence tolerances for each continuous subproblem optimization according to the maximum constraint violation obtained from the first iteration of each subproblem optimization in order to reduce the total number of function evaluations needed to reach the discrete optimal solution. The proposed tolerance scheme is integrated with five branching order options. The comparative performance test results using the ten combinations of the five branching orders and two convergence tolerance schemes show that the suggested non-uniform convergence tolerance scheme is obviously superior to the uniform one. The results also show that the branching order option using the minimum clearance difference method performed best among the five branching order options. Therefore, we recommend using the "minimum clearance difference method" for branching and the "non-uniform convergence tolerance scheme" for solving discrete optimization problems.

• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.53-63
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• 1985

This paper presents a multi-costraint optimization model for redundant system reliability. The optimization model is usually formulated as a nonlinear integer programming (NIP) problem. This paper reformulates the NIP problem into a linear integer programming (LIP) problem. Then an efficient 'Branch and Straddle' algorithm is proposed to solve the LIP problem. The efficiency of this algorithm stems from the simultaneous handling of multiple variables, unlike in ordinary branch and bound algorithms. A numerical example is given to illustrate this algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.169-180
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• 2015

Recently, scheduling problems with position-dependent processing times have received considerable attention in the literature, where the processing times of jobs are dependent on the processing sequences. However, they did not consider cases in which each processed job has different learning or aging ratios. This means that the actual processing time for a job can be determined not only by the processing sequence, but also by the learning/aging ratio, which can reflect the degree of processing difficulties in subsequent jobs. Motivated by these remarks, in this paper, we consider a two-agent single-machine scheduling problem with linear job-dependent position-based learning effects, where two agents compete to use a common single machine and each job has a different learning ratio. Specifically, we take into account two different objective functions for two agents: one agent minimizes the total weighted completion time, and the other restricts the makespan to less than an upper bound. After formally defining the problem by developing a mixed integer non-linear programming formulation, we devise a branch-and-bound (B&B) algorithm to give optimal solutions by developing four dominance properties based on a pairwise interchange comparison and four properties regarding the feasibility of a considered sequence. We suggest a lower bound to speed up the search procedure in the B&B algorithm by fathoming any non-prominent nodes. As this problem is at least NP-hard, we suggest efficient genetic algorithms using different methods to generate the initial population and two crossover operations. Computational results show that the proposed algorithms are efficient to obtain near-optimal solutions.