• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.65-69
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• 1990

Two different algorithms for traveling salesman problem(TSP) will be discussed. One is the engineering approach to the TSP. The other one is Branch-and-Bound algorithm to take advantage of the special structure of combinational problems. Also a generalization of TSP will be presented.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.4
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• pp.51-60
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• 2007

In this study, we consider the minimum ADM problem which is the fundamental problem for the cost-effective design of SONET ADM embedded in WDM ring networks. To minimize the number of SONET ADMs, efficient algorithms for the routing and wavelength assignment are needed. We propose a mathematical model based on the graph theory for the problem and propose a branch-and-price approach to solve the suggested model effectively within reasonable time. By exploiting the mathematical structure of ring networks, we developed polynomial time algorithms for column generation subroutine at branch-and-bound tree. In a computer simulation study, the suggested approach can find the optimal solution for sufficient size networks and shows better performance than the greedy heuristic method.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.1-12
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• 2012

In this paper, we report a case study on the common due-date assignment and scheduling problem in a paper remanufacturing system that produces corrugated cardboards using collected waste papers for a given set of orders under the make-to-order (MTO) environment. Since the system produces corrugated cardboards in an integrated process and has sequence-dependent setups, the problem considered here can be regarded as common due-date assignment and sequencing on a single machine with sequence-dependent setup times. The objective is to minimize the sum of the penalties associated with due-date assignment, earliness, and tardiness. In the study, the earliness and tardiness penalties were obtained from inventory holding and backorder costs, respectively. To solve the problem, we adopted two types of algorithms: (a) branch and bound algorithm that gives the optimal solutions; and (b) heuristic algorithms. Computational experiments were done on the data generated from the case and the results show that both types of algorithms work well for the case data. In particular, the branch and bound algorithm gave the optimal solutions quickly. However, it is recommended to use the heuristic algorithms for large-sized instances, especially when the solution time is very critical.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.272-281
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• 1988

The problem of optimal transmission system planning is to find the most economical locations and time of transmission line construction under the various constraints such as available rights-of-way, finances, the technical characteristics of power system, and the reliability criterion of power supply, and so on. In this paper the constraint of right-of-way is represented as a finite set of available rights-of-way. And the constructed for a unit period. The electrical constraints are represented in terms of line overload and steady state stability margin. And the reliability criterion is dealt with the suppression of failure cost and with single-contingency analysis. In general, the transmission planning problem requires integer solutions and its objective function is nonlinear. In this paper the objective function is defined as a sum of the present values of construction cost and the minimum operating cost of power system. The latter is represented as a sum of generation cost and failure cost considering the change of yearly load, economic dispatch, and the line contingency. For the calculation of operating cost linear programming is adopted on the base of DC load flow calculation, and for the optimization of main objective function nonlinear Branch-and-Bound algorithm is used. Finally, for improving the efficiency of B & B algorithm a new sensitivity analysis algorithm is proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.78-101
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• 2017

High-quality industrial control is critical to ensuring production quality, reducing production costs, improving management levels and stabilizing equipment and long-term operations. WiFi-based Long Distance (WiLD) networks have been used as remote industrial control networks. Real-time performance is essential to industrial control. However, the original mechanism of WiLD networks does not minimize end-to-end delay and restricts improvement of real-time performance. In this paper, we propose two algorithms to obtain the transmitting/receiving phase cycle length for each node such that real time constraints can be satisfied and phase switching overhead can be minimized. The first algorithm is based on the branch and bound method, which identifies an optimal solution. The second is a fast heuristic algorithm. The experimental results show that the execution time of the algorithm based on branch and bound is less than that of the heuristic algorithm when the network is complex and that the performance of the heuristic algorithm is close to the optimal solution.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.70-79
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• 2010

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2187-2195
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• 2017

In order to solve the AC optimal power flow (OPF) problem considering the generators' on/off status, it is necessary to model the problem as mixed-integer nonlinear programming (MINLP). Because the computation time to find the optimal solution to the mixed-integer AC OPF problem increases significantly as the system becomes larger, most of the existing solutions simplify the problem either by deciding the on/off status of generators using a separate unit commitment algorithm or by ignoring the minimum output of the generators. Even though this kind of simplification may make the overall computation time tractable, the results can be significantly erroneous. This paper proposes a novel algorithm for the mixed-integer AC OPF problem, which can provide a near-optimal solution quickly and efficiently. The proposed method is based on a combination of the outer approximation method and the relaxed AC OPF theory. The method is applied to a real-scale power system that has 457 generators and 2132 buses, and the result is compared to the branch-and-bound (B&B) method and the genetic algorithm. The results of the proposed method are almost identical to those of the compared methods, but computation time is significantly shorter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3180-3199
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• 2013

While non-predefined object segmentation (NDOS) distinguishes an arbitrary self-assumed object from its background, predefined object segmentation (DOS) pre-specifies the target object. In this paper, a new and novel method to segment predefined objects is presented, by globally optimizing an orientation-based objective function that measures the fitness of the object boundary, in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shape. The orientation factor provides robust distinctness for target objects. By considering the order of transformation elements, and their dependency on the derived over-segmentation outcome, the domain of translations and scales is efficiently discretized. A branch and bound algorithm is used to determine the transformation parameters of a shape model corresponding to a target object in an image. The results tested on the PASCAL dataset show a considerable achievement in solving complex backgrounds and unclear boundary images.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.2
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• pp.44-50
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• 2007

This paper deals with the problem of scheduling jobs and rate-modifying activities on parallel machines. A rate-modifying activity is an activity that changes the production rate of equipment such as maintenance and readjustment. If a job is scheduled after the rate-modifying activity, then the processing time varies depending on the modifying rate of the activity. In this study, we extend the single machine problem to parallel machines problem and propose algorithms is to schedule the rate-modifying activities and jobs to minimize the makespan on parallel machines which is NP-hard. We propose a branch and bound algorithm with three lower bounds to solve medium size problems optimally. Also we develop three heuristics, Modified Longest Processing Time, Modified MULTIFIT and Modified COMBINE algorithms to solve large size problems. The test results show that branch and bound algorithm finds the optimal solution in a reasonable time for medium size problems (up to 15 jobs and 5 machines). For large size problem, Modified COMBINE and Modified MULTIFIT algorithms outperform Modified LPT algorithm in terms of solution quality.

• Journal of Korean Port Research
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• v.10 no.2
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• pp.7-15
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• 1996

A berth assignment problem has a direct impact on assessment of charges made to ships and goods. A berth can be assigned to incoming vessels and operated in tow different ways: as a common user berth, as a preference berth. A common user berth is a berth that any ship calling at a port may be permitted to use according to her time of arrival and to priorities as determined by the port authority. In this paper, we concerned with various types of mathematical programming models for a berth assignment problem to achive an efficient berth operation. In this paper, we focus on a reasonable berth assignment programming in a public container terminal in consideration of trade-off between server and user. We propose a branch and bound algorithm & heuristic algorithm for solving the problem. We suggest three models of berth assignment to minimizing the objective functions such as total port time, total berthing time and maximum berthing time by using a revised Maximum Position Shift(MPS) with which the trade-off between servers and users can be considered. The berth assignment problem is formulated by min-max and 0-1 integer programming and developed heuristic algorithm to solve the problem more easily instead of branch and bound method. Finally, we gave the numerrical solutions of the illustrative examples.