• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2007.11a
• /
• pp.16-19
• /
• 2007

At an integrated steel mill, raw materials such as coal and iron ore are discharged by ships through multiple unloaders. The discharged raw material is then transported to storage yards through multiple routes established simultaneously on a fairly complicated belt conveyer network. Formulating an efficient unloading schedule is a quite cumbersome task due to the insufficient number of berths and unloaders as well as the potential conflict among routes being used simultaneously. In this paper, we propose a solution approach to the scheduling problem and describe the prototype system that we built as an implementation of our approach.

• Korean Management Science Review
• /
• v.30 no.3
• /
• pp.99-111
• /
• 2013

This paper studies the scheduling problem of storing and retrieving assembly blocks in a temporary storage yard. The objective is to minimize the number of relocations of blocks while the constraints for storage and retrieval time windows are satisfied. We present an integer programming model based on multi-commodity network flows, and the three revised models based on the properties of the problem. We show that the revised models are more efficient than the generic model through the numerical experiments.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.20 no.1
• /
• pp.115-130
• /
• 1995

This paper considers a single machine nonpreemptive scheduling problem with a given common due date. In the problem, the optimal job sequence is sought to minimize the sum of earliness/tardiness and flow time measures in the situation where all jobs are available at time zero, and weights per unit length of earliness/tardiness and flow time are V and W, respectively. Some dominant solution properties are characterized to deriva both an optimal starting time for an arbitrary sequence and sequence improvement rules. The optimal schedule is found to the case W .geq. V/. By the way, it is difficult to find the optimal schedule for the case W < V. Therefore, the derived properties are put on together to construct a heuristic solution algorithm for the case W < V, and its effectiveness is rated at the mean relative error of about 3% on randomly generated numerical problems.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.24 no.3
• /
• pp.73-82
• /
• 1999

In this paper, we address a single machine non-preemptive n-job scheduling problem to minimize the sum of earliness and tardiness with different release times and due dates. To solve the problem, we propose a genetic algorithm with new crossover and mutation operators to find the job sequencing. For the proposed genetic algorithm, the optimal pair of crossover and mutation rates is investigated. To illustrate the suitability of genetic algorithm, solutions of genetic algorithm are compared with solutions of exhaustive enumeration method in small size problems and tabu search method in large size problems. Computational results demonstrate that the proposed genetic algorithm provides the near-optimal job sequencing in the real world problem.

• Korean Management Science Review
• /
• v.17 no.1
• /
• pp.135-144
• /
• 2000

This paper describes a scheduling problem of the panel block assembly shop in a shipbuilding industry. Because the shipbuilding is a labor intensive industry the most important consideration in a panel block assembly shop is the workload balancing. which balances man-hour weight and welding length and so on. It should be determined assembly schedule and workstation considering a daily load balancing and a workstation load balancing simultaneously. To solve the problem we develop a hybrid genetic algorithm. Hybrid genetic algorithm proposed in this paper consists of two phases. The first phase uses the heuristic method to find a initial feasible solution which provides a useful information about optimal solution. The second phase proposes the genetic algorithm to derive the optimal solution with the initial population consisting of feasible solutions based on the initial solution. Finally we carried out computational experiments for this load balancing problem which indicate that developed method is effective for finding good solutions.

• Korean Management Science Review
• /
• v.17 no.1
• /
• pp.41-54
• /
• 2000

in the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.21 no.1
• /
• pp.147-161
• /
• 1996

Generally the Multiprocessor Scheduling (MPS) problem is difficult to solve because of the precedence of the tasks, and it takes a lot of time to obtain its optimal solution. Though Genetic Algorithm (GA) does not guarantee the optimal solution, it is practical and effective to solve the MPS problem in a reasonable time. The algorithm developed in this research consists of a improved GA and GP/MISF (Critical Path/Most Immediate Successors First). An efficient genetic operator is derived to make GA more efficient. It runs parallel CP/MISF with GA to complement the faults of GA. The solution by the developed algorithm is compared with that of CP/MISF, and the better is taken as a final solution. As a result of comparative analysis by using numerical examples, although this algorithm does not guarantee the optimal solution, it can obtain an approximate solution that is much closer to the optimal solution than the existing GA's.

• Korean Management Science Review
• /
• v.13 no.2
• /
• pp.163-175
• /
• 1996

This research shows that fuzzy set theory can be useful in modeling and solving flow shop scheduling problems with uncertain processing times and illustrates a method for solving job sequencing problem which the opinions of experts disagree in each processing time. In this study, FCDS (Fuzzified Campbell-Dudek-Smith) algorithm and FNEH (Fuzzified Nawaz-Enscope-Ham) algorithm are proposed to improve the fuzzified Branch & Bound algorithm that requires long run-time and computational complexities to find the optimal sequence. These proposed algorithms are also designed to treat opinions of experts. In this paper, Fuzzy processing times are expressed as triangular fuzzy numbers and comparison method use Lee-Li method and ranking method based on the dominance property. On the basis of the proposed method, an example is presented.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.04a
• /
• pp.310-313
• /
• 1996

Mathematical programming method for finding optimal solution of job shop scheduling is inadequate to real situation because fo too much computation time. In contrast, dispatching rule is helpful for reducing compuation time but is not guaranted to find optimal solution. The purpose of this paper is to develop a new dispatching rule and procedure to minimize mean flow time whose result is near the optimal solution for job shop scheduling. First step is to select machine which have shortest finishing operation time among the schedulable operations. Second step is to select operation with regard to estimated remaining operation time. The suggested rule is compared with nondelay and MWKR rule for three examples, and is confirmed to be most effective to minimize mean flow time.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.10a
• /
• pp.307-309
• /
• 1996

This paper analyses a deterministic scheduling problem concerned with manufacturing two types of components at a pre-assembly stage which consists of two independent feeding machines each producing its own type of component. Each type represents a unique component which may have variations in its size or quality. Therefore, the completion time of each component depends on both its type and quality (size) variations. Such manufactured components are subsequently assembled into various component dependent products. The problem has the objective measure of minimizing the total weighted completion time of a finite number of jobs(products) where the completion time of each job is measured by the latest completion time of its two components at the pre-assembly stage. The problem is shown to be NP-complete in the strong sense. A WSPT rule coupled with a machine-aggregation idea is developed for good heuristics which show the error bound of 2.