• 경영과학
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• 제17권2호
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• pp.175-187
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• 2000

The stochastic vehicle routing problem (VRP) is a problem of growing importance since it includes a reality that the deterministic VRP does not have. The stochastic VRP arises whenever some elements of the problem are random. Common examples are stochastic service quantities and stochastic travel times. The solution methodologies for the stochastic VRP are very intricate and regarded as computationally intractable. Even heuristics are hard to develope and implement. On possible way of solving it is to apply a solution for the deterministic VRP. This paper presents a performance evaluation of four simple heuristic for the deterministic VRP is a stochastic environment. The heuristics are modified to consider the time window constraints. The computational results show that some of them perform very well in different cases of the stochastic VRP.

• Industrial Engineering and Management Systems
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• 제14권1호
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• pp.11-21
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• 2015

The purpose of this research is to develop algorithms using the Differential Evolution Algorithm (DE) to solve a multi-objective, sources and stages location-allocation problem. The development process starts from the design of a standard DE, then modifies the recombination process of the DE in order improve the efficiency of the standard DE. The modified algorithm is called modified DE. The proposed algorithms have been tested with one real case study (large size problem) and 2 randomly selected data sets (small and medium size problems). The computational results show that the modified DE gives better solutions and uses less computational time than the standard DE. The proposed heuristics can find solutions 0 to 3.56% different from the optimal solution in small test instances, while differences are 1.4-3.5% higher than that of the lower bound generated by optimization software in medium and large test instances, while using more than 99% less computational time than the optimization software.

• 한국경영과학회지
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• 제30권3호
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• pp.67-80
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• 2005

This paper deals with a container terminal where containers are discharged by quay cranes from a ship and transported by a fleet of vehicles to the terminal yard. Since container terminals are fully utilized in general, It is important to increase terminal throughput by discharging the containers out of the ship without any delay, At the operational level, it should be decided which vehicle transports which container. The vehicle dispatching decision should be carefully made since the container discharging time increases when the quay cranes wait idle for the vehicles. This paper presents vehicle dispatching heuristics with the objective of minimizing the total container discharging time. The heuristics are based on a network flow model and a look-ahead concept. Through some experiments, the performance of the dispatching methods is evaluated.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.51-54
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• 1996

We deal with a design problem of assembly/disassembly (AD) systems with finite buffer capacities where the times between failures, the times to repair, and the processing times are exponentially distributed with different parameter values. We present a solution procedure for finding the minimum cost configuration which achieves a desired throughput rate for an AD system. The configuration is defined by the types of machines to be used and capacities of buffers in the AD system. Results of computational experiments on randomly generated test problems show that the proposed heuristics give relatively good configurations in a reasonable amount of time.

• 한국경영과학회지
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• 제24권3호
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• pp.27-37
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• 1999

In just-in-time production systems, U-shaped production lines rather than traditional straight lines are often adopted since they have some advantages. The advantages of U-lines over straight lines are that the workstations required can be reduced and the necessary number of workers can be easily adjusted when the demand rates are changed. In this paper, we present a new heuristic based on genetic algorithm to improve the workload smoothness in the U-line. In the proposed algorithm, a new genetic representation is developed which is specific to the problem being solved. To enhance the capability of searching good solutions, genetic operators are designed by using the problem-specific information and heuristics. Extensive experiments are carried out on well-known test-bed problems in the literature to verify the performance of our algorithm. The computational results show that our algorithm is a promising alternative to existing heuristics.

• Steel and Composite Structures
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• 제24권1호
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• pp.129-140
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• 2017

Structural optimization is one of the popular and active research areas in the field of structural engineering. In the present study, the newly developed moth-flame optimization (MFO) algorithm and its enhanced version termed as enhanced moth-flame optimization (EMFO) are employed to implement the optimization process of planar and 3D steel frame structures with discrete design variables. The main inspiration of this optimizer is the navigation method of moths in nature called transverse orientation. A number of benchmark steel frame optimization problems are solved by the MFO and EMFO algorithms and the results are compared with those of other meta-heuristics. The obtained numerical results indicate that the proposed EMFO algorithm possesses better computational performance compared with other existing meta-heuristics.

• Journal of Computing Science and Engineering
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• 제10권1호
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• pp.9-20
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• 2016

Several task clustering heuristics are proposed for allocating tasks in heterogeneous systems to achieve a good response time in data intensive jobs. However, one of the challenging problems is the process in task scheduling after task allocation by task clustering. We propose a task scheduling method after task clustering, leveraging worst schedule length (WSL) as an upper bound of the schedule length. In our proposed method, a task in a WSL sequence is scheduled preferentially to make the WSL smaller. Experimental results by simulation show that the response time is improved in several task clustering heuristics. In particular, our proposed scheduling method with the task clustering outperforms conventional list-based task scheduling methods.

• 대한안전경영과학회지
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• 제12권1호
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• pp.97-104
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• 2010

Expanded muti-source Weber problem (EWP), which introduced in this paper, is a reverse logistics network design problem to minimize the total transportation cost from customers thorough regional center to central center. Decision factor of EWP are the locations of regional centers and a central center. We introduce a GRASP heuristics for the EWP. In the suggested GRASP, an expanded iterative location allocation method (EILA) is introduced based on the Cooper's iterative location allocation method[3]. For the initial solution of GRASP, allocation first seed (AFSeed) and location first seed (LFSeed) are developed. The computational experiment for the objective value shows that the LFSeed is better than the AFSeed. Also the calculating time of the LFSeed is better than that of the AFSeed.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.1065-1070
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• 2003

Facility Layout Planning is concerned with how to arrange facilities necessary for production in a given space. Its objective is often to minimize the total sum of all material flows multiplied by the distance among facilities. FLP belongs to NP complete problem; i.e., the number of possible layout solutions increases with the increase of the number of facilities. Thus, meta heuristics such as Genetic Algorithm (GA) and Simulated Annealing have been investigated to solve the FLP problems. However, one of the biggest problems which lie in the existing meta heuristics including GA is hard to find an appropriate combinations of parameters which result in optimal solutions for the specific problem. The Ant System algorithm with elitist and ranking strategies is used to solve the FLP problem as an another good alternative. Experimental results show that the AS algorithm is able to produce the same level of solution quality with less sensitive parameters selection comparing to the ones obtained by applying other existing meta heuristic algorithms.

• 제어로봇시스템학회논문지
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• 제1권2호
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• pp.119-126
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• 1995

The purpose of this study is to develop the technique of energy recovery and energy saving by using the optimization of heat exchanger network synthesis. This article proposes a new method of determining the optimal target of a heat exchanger network synthesis problem of which data feature multiple pinch points. The system separation method we suggest here is to subdivide the original system into independent subsystems with one pinch point. The optimal cost target was evaluated and the original pinch rules at each subsystem were employed. The software developed in this study was applied to the Alko prosess, which is an alcohol production process, for the synthesis of heat exchanger network. It was possible to save about 15% of the total annual cost.