• IE interfaces
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• v.24 no.4
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• pp.281-294
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• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.187-200
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• 1998

This paper presents an original approach for solving short-term power scheduling in extended power system with two fuels in a unit and a limited fuel using Lagrangian relaxations. The underlying model incorporates the full set of costs and constraints including setup, production, ramping, and operational status, and takes the form of a mixed integer nonlinear control problem. Moreover, the mathematical model developed includes two fuels in a unit and a limited fuel, regulation reserve requirements of prespecified group of units. Lagrangian relaxation is used to disaggregate the model by generator into separate subproblems which are then solved with a nested dynamic program including empirical knowledges. The strength of the methodology lies partially in its ability to construct good feasible solutions from information provided by the dual. Thus, the need for branch-and-bound is eliminated. In addition, the inclusion of two fuels in a unit and a limited fuel provides new insight into the limitations of current techniques. Computational experience with the proposed algorithm indicates that Problems containing up to 23 units including 8 unit used two fuels and 24 time periods can be readily solved in reasonable times. Duality gaps of less than 4％ were achieved.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.4
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• pp.113-128
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• 2016

This paper proposes a Bi-level Genetic Algorithm for the Fixed Charge Transportation Problem with Non-linear Unit Cost. The problem has the property of mixed integer program with non-linear objective function and linear constraints. The bi-level procedure consists of the upper-GA and the lower-GA. While the upper-GA optimize the connectivity between each supply and demand pair, the lower-GA optimize the amount of transportation between the pairs set to be connected by the upper-GA. In the upper-GA, the feasibility of the connectivity are verified, and if a connectivity is not feasible, it is modified so as to be feasible. In the lower-GA, a simple method is used to obtain a pivot feasible solution under the restriction of the connectivity determined by the upper-GA. The obtained pivot feasible solution is utilized to generate the initial generation of chromosomes. The computational experiment is performed on the selected problems with several non-linear objective functions. The performance of the proposed procedure is analyzed with the result of experiment.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.145-156
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• 2015

Incorporation of individual learning and forgetting behaviors within worker-task assignment models produces a mixed integer nonlinear program (MINLP) problem, which is difficult to solve as a NP hard due to its nonlinearity in the objective function. Previous studies commonly assume homogeneity among workers in workforce scheduling that takes account of learning and forgetting characteristics. This paper expands previous researches by considering heterogeneous individual learning/forgetting, and investigates the impact of worker heterogeneity in initial expertise, steady-state productivity, learning and forgetting on system performance to assist manager's decision-making in worker-task assignments without tackling complex MINLP models. In order to understand the performance implications of workforce heterogeneity, this paper examines analytically how heterogeneity in each of the four parameters of the exponential learning and forgetting (L/F) model affects system performance in three cases : consecutive assignments with no break, n breaks of s-length each, and total b break-periods occurred over T periods. The study presents the direction of change in worker performance under different assignment schedules as the variance in initial expertise, steady-state productivity, learning or forgetting increases. Thus, it implies whether having more heterogenous workforce in terms of each of four parameters in the L/F model is desired or not in different schedules from the perspective of system productivity measurement.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1681-1693
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• 1997

In a distributed system, the simple file allocation problem determines the placement of copies of a file, so as to minimize the operating costs. The simple file allocation problem assumes the cost parameters to be fixed. In practice, these parameters change over time. In this research, dynamic file allocation problem for both single and multiple files are considered, which account for these changing parameters. A model for dynamic file allocation problem is formulated as a mixed integer program for which Lagrangian relaxation based branch-and-bound algorithm is developed. This algorithms is implemented and its efficiency is tested on medium to large test problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3204-3217
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• 2023

In this paper, the downlink of the multicast based spatial modulation systems is investigated. Specifically, physical layer multicasting is introduced to increase the number of access users and to improve the communication rate of the spatial modulation system in which only single radio frequency chain is activated in each transmission. To minimize the bit error rate (BER) of the multicast based spatial modulation system, a joint optimizing algorithm of antenna selection and multicast precoding is proposed. Firstly, the joint optimization is transformed into a mixed-integer non-linear program based on single-stage reformulation. Then, a novel iterative algorithm based on the idea of branch and bound is proposed to obtain the quasioptimal solution. Furthermore, in order to balance the performance and time complexity, a low-complexity deflation algorithm based on the successive convex approximation is proposed which can obtain a sub-optimal solution. Finally, numerical results are showed that the convergence of our proposed iterative algorithm is between 10 and 15 iterations and the signal-to-noise-ratio (SNR) of the iterative algorithm is 1-2dB lower than the exhaustive search based algorithm under the same BER accuracy conditions.

• Journal of the military operations research society of Korea
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• v.36 no.1
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• pp.15-27
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• 2010

Fire sequencing problem is to find a sequence of firing on the targets. The latest, because the korea artillery force is inferior in number as compared with north korea force. It is an important question to give a fatal damage to the enemy force by using prompt and accurate fire in order to overcome the lack of artillery force. Minimizing the fire finishing time will secure the adapt ability in tactical operation. In this paper, we developed a mathematical model to do allocation the fire on the targets to decrease to total fire operation time. In order to work out the fire sequencing problem, MIP is developed and the optimum solution is obtained by using ILOG OPL. If this analytical model is applied to the field artillery unit, it will improve the artillery fire force enhancement.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.51-58
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• 2010

Wireless Mesh Network has drawn much attention due to wide area service coverage with low system cost. However, there is a bottleneck problem in wireless mesh network since the traffic is aggregated into a gateway. Placement of multi-radio can easy the bottleneck problem, but without careful design it results in unnecessary system cost increasement. In this paper, we propose a system cost minimization through differential antenna placement where optimum antenna placement is determined by the required wireless link capacity. With CPLEX program, optimum number of antennae is determined as a function of local user traffic and gateway capacity. From numerical analysis, it is confirmed that our proposed model can solve bottleneck problem, and at the same time save the system cost.

• Industrial Engineering and Management Systems
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• v.11 no.3
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• pp.233-240
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• 2012

The implementation of business process management (BPM) systems in large number of business organizations transforms BPM system into such a level of maturity and tends to collect large repositories of business process (BP) models. This issue encourages BP flexibility that leads to a large number of process variants derived from the same model, but differing in structure, to be stored in the large repositories of BP models. Therefore, the repositories may include thousands of activities and related business objects with variation of requirements and quality of service. It is a common practice to customize processes from reference processes or templates in order to reduce the time and effort required to design and deploy processes on all levels. In order to address redundancy and underutilization problems, a generic process model, called as reference BP, is absolutely necessary to cover the best of process variants. This study aims to develop multiple-objective business process genetic algorithm (MOBPGA) to find a set of non-dominated (Pareto) solutions of business reference model to enhance conventional approach which considered only a single objective on creating BP reference model by using proximity score measurement. A mixed-integer linear program is constructed to evaluate performance of the proposed MOBPGA on small-scale problems by using standard measures for multiple-objective techniques. The results will show the viability of applying MOBPGA in terms of simultaneously maximizing proximity score measurement, minimizing total duration, and total costs of the selected reference model.

• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.105-115
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• 2007

It is essential to give a fatal damage to the enemy force by using prompt and accurate fire in order to overcome the lack of artillery force. During the artillery fire operations, minimizing the firing time will secure the adapt ability in tactical operation. In this paper, we developed a mathematical model to schedule the artillery fire on the multiple targets to decrease total fire operation time. To design a program to describe a real firing situation, we consider many possible circumstances of changes such as commander's intention, firing constraints, target priority, and contingency plan to make a fire plan in an artillery unit. In order to work out the target sequencing problem, MIP is developed and the optimum solution is obtained by using ILOG OPL. If this analytical model is applied to a field artillery unit, it will improve the efficiency of the artillery fire force operations.