• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.13-18
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• 1986

This paper is concerned with flow-shop permutation scheduling problem. This paper presents an algorithm for the minimum makespan sequence. The efficiency of proposed algorithm is demonstrated by comparisons with the existing algorithms: Johnson's, branch & bound method, and heuristic algorithms. The proposed algorithm is more effective than the other algorithms. A numerical example is given to illustrate the procedure.

• 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.

• 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.

• Korean Management Science Review
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• v.33 no.2
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• pp.75-87
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• 2016

Quality function deployment (QFD) is a widely adopted customer-oriented product development methodology by analyzing customer requirements. It is a main activity in QFD planning process to determine the optimal values of the technical attributes (TAs) so as to achieve the customer requirements (CRs) from the House of Quality (HoQ). In most of the previous research, all the TAs in QFD are assumed to have either continuous or discrete values. In the real world applications, the continuous TAs and the discrete TAs are often mixed in QFD. In this paper, a mixed integer linear programming model is formulated to obtain the optimal values for the continuous TAs and the discrete TAs in QFD planning as well as Branch and Bound (B and B) algorithm is proposed as the solution approach. Finally, the proposed model and solution approach are illustrated with an office chair under multi-segment market, and the sensitivity analysis is performed to study how the proposed model and its solutions respond to the variation for the two elements which are budget and CRs' weights.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.33-49
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• 1998

In order to improve the performance of relational databases, one has to reduce the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to reduce the number of disk I/O accesses by vertically partitioning relation into fragments and allowing attribute replication to fragments if necessary. When zero-one integer programming model is solved by the branch-and-bound method, it requires much computing time to solve a large sized problem. Therefore, heuristic solutions using genetic algorithm(GA) are presented. GA in this paper adapts a few ideas which are different from traditional genetic algorithms, for examples, a rank-based sharing fitness function, elitism and so on. In order to improve performance of GA, a set of optimal parameter levels is determined by the experiment and makes use of it. As relations are vertically partitioned allowing attribute replications and saved in disk, an attribute replicating vertical partition method by GA can attain less access cost than non-attribute-replication one and require less computing time than the branch-and-bound method in large-sized problems. Also, it can acquire a good solution similar to the optimum solution in small-sized problem.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.171-176
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• 2021

This paper deals with bid evaluation problem that chooses the vendors and quantity with minimum purchasing cost for bid information of setup cost and unit price. For this problem, the branch-and-bound(BB) and branch-and-cut(BC) methods are well-known. But these methods can be fail to obtain the optimal solution. This paper gets the initial feasible solution with procuring quantity assignment principle in accordance with the unit price or setup cost rank-first. Then procuring quantity moving optimization(vendor change) is execute take account of unit price or setup cost rank. As a result of experimentation, the propose algorithm is significantly lower compared to BB and BC.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.1
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• pp.27-30
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• 1983

The purpose of this paper is to find a new method for the warehouse location problem. Akinc and Khumatvala developed a branch and bound algorithm for a one-stage problem, that is, plants and warehouses are at the same location. This paper extends this method to a two-stage problem, that is, plants, warehouses and users are located at different sites, and further this paper allows direct flows from plants to users. The new method is tested at Perkins-Elmer. The test shows that the algorithm is efficient.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.99-104
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• 2002

This paper addresses a problem of machining route selection and determination of input quantity with yield in multi-stage flexible flow system. The problem is formulated as nonlinear programing and the proposed model is solved by genetic algorithm(GA) approach. The effectiveness of the proposed GA approach is evaluated through comparisons with the optimal solution obtained from the branch and bound for the same problem.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1123-1128
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• 1993

In this paper, utilizing the line balancing algorithm proposed to deal with various situations of automated assembly line, the optimal solution can be derived by the branch and bound method of analysis. By the application of line balancing algorithm to telephone assembly line, thoughput is improved by 3.38%. Therefore, in the proposed line, blicking phenomena were reduced and smooth line-flow was achieved, and uniform distribution of utilization rate of each machine is obtained.