• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.81-87
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• 1999

This paper discusses a bicriterion approach to sequencing with time/cost trade-offs. The first problem is to minimize the total flow time and the maximum tardiness. And second is to the maximum tardiness and resource allocation costs. This approach, which produces an efficient flintier of possible schedules, has the advantage that it does not require the sequencing criteria to be measurable in the same units as the m allocation cost. The basic single machine model is used to treat a class of problems in which the sequencing objective is to minimize the maximum completion penalty. It is further assumed that resource allocation costs can be represented by linear time/cost function.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.823-835
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• 2019

Purpose: This study deals with a production planning and scheduling problem to minimize the total weighted tardiness on hybrid flow shop with sets of non-identical parallel machines on stages, where parallel machines in the set are dedicated to perform specific subsets of jobs and sequence-dependent setup times are also considered. Methods: A two-stage approach, that applies MILP model in the 1st stage and dispatching rules in the 2nd stage, is proposed in this paper. The MILP model is used to assign jobs to a specific machine in order to equalize the workload of the machines at each stage, while new dispatching rules are proposed and applied to sequence jobs in the queue at each stage. Results: The proposed two-stage approach was implemented by using a commercial MILP solver and a commercial simulation software and a case study was developed based on the spark plug manufacturing process, which is an automotive component, and verified using the company's actual production history. The computational experiment shows that it can reduce the tardiness when used in conjunction with the dispatching rule. Conclusion: This proposed two-stage approach can be used for HFS systems with dedicated machines, which can be evaluated in terms of tardiness and makespan. The method is expected to be used for the aggregated production planning or shop floor-level production scheduling.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.47-50
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• 2004

This paper deals with the problem of batching and scheduling of jobs whose processing times are different respectively But, they are given as not the exact value but the range from the lower limits to the upper, which makes it possible to group jobs into batches. The grouping of jobs is desirable because of the capability of the batch processor to accommodate several jobs at once. The time required to process the jobs in any batch depends on their lower limit processing times. Once processing is initiated on a batch processor, the batch cannot be interrupted, nor can other jobs be started. And all jobs are assumed to be simultaneously available. This paper develops the model to describe these situation and a heuristic method to minimize its total tardiness.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1998.10a
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• pp.731-740
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• 1998

This paper discusses a brcriterion approachto sequencing with time/cost trade-offs. The first problem is to minimize the total flow time and the maximum tardiness. And second is to the maximum tardiness and resource allocation costs. This approach , which produces an efficient frontier of possible schedules, has the advantage that it does not require the sequencing criteria to be measurable in the same units as the resource allocation cost. The basic single machine model is used to treat a class of problems in which the sequencing objective is to minimize the maximum completion penalty. It is further assumed that resource allocation costs can be represented by linear time/cost function.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.90-93
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• 2000

This paper presents job scheduling for non-identical parallel machines using Simulated Annealing (SA). The scheduling problem accounts for allotting work parts of L lots into M parallel machines, where each lot is composed of N homogeneous jobs. Some lots may have different jobs while every job within each lot has common due date. Each machine has its own performance and set up time according to the features of the machine, and also by job types. A meta-heuristic, SA, is applied in this study to determine the job sequences of the scheduling problem so as to minimize total tardiness of due. The SA method is compared with a conventional steepest descent(SD) algorithm that is a typical tool for finding local optimum. The comparison shows the SA is much better than the SD in terms tardiness while SA takes longer , but acceptable time.

• Journal of the Korea Safety Management & Science
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• v.8 no.4
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• pp.195-204
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• 2006

This paper deals with a batch processor model in which the batch processing speed depends on the jobs assigned to the batch. Each job is completed by accomplishing its required job processing quantity which is calculated as job speed product processing time. Its speed is given as not the exact value but the range. Thus the batch sets are constructed by the jobs which hold the speed in common. And the batch sets are processed as soon as possible. We developed the model to described the problem situation and adopt the total tardiness as the decision criterion.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.1
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• pp.140-146
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• 2005

This study presents the new dispatching rules of job shop scheduling with auxiliary resource constraint to improve the schedule performance measures related to completion time and due dates. The proposed dispatching rules consider the information of total work remaining and machine utilization to decrease mean flowtime and mean tardiness. The results of computer experiments show that those schedule performances are significantly improved by using the new dispatching rules. The results provide guidance for the researchers and practitioners of auxiliary resource constrained job shop scheduling to decrease mean flowtime and mean tardiness.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.266-279
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• 2009

This paper focuses on the problem of scheduling wafer lots with limited waiting times between pairs of consecutive operations in a semiconductor wafer fabrication facility. For the problem of minimizing total tardiness of orders, we develop a priority rule based scheduling method in which a scheduling decision for an operation is made based on the states of workstations for the operation and its successor or predecessor operation. To evaluate performance of the suggested scheduling method, we perform simulation experiments using real factory data as well as randomly generated data sets. Results of the simulation experiments show that the suggested method performs better than a method suggested in other research and the one that has been used in practice.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.3
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• pp.254-262
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• 2014

Radar task scheduling deals with the assignment of task to efficiently enhance the radar performance on the limited resource environment. In this paper, total weighted tardiness is adopted as the objective function of task scheduling in operation of multiple multi-function radars. To take into account real-time implementability, heuristic index-based methods are presented and investigated. Numerical simulations for generic search and track scenarios are performed to evaluate the proposed methods, in particular investigating the effectiveness of multi-radar operation concepts.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.151-160
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• 2013

In the past decades, several algorithms based on evolutionary approaches have been proposed for solving job shop scheduling problems (JSP), which is well-known as one of the most difficult combinatorial optimization problems. Most of them have concentrated on finding optimal solutions of a single objective, i.e., makespan, or total weighted tardiness. However, real-world scheduling problems generally involve multiple objectives which must be considered simultaneously. This paper proposes an efficient particle swarm optimization based approach to find a Pareto front for multi-objective JSP. The objective is to simultaneously minimize makespan and total tardiness of jobs. The proposed algorithm employs an Elite group to store the updated non-dominated solutions found by the whole swarm and utilizes those solutions as the guidance for particle movement. A single swarm with a mixture of four groups of particles with different movement strategies is adopted to search for Pareto solutions. The performance of the proposed method is evaluated on a set of benchmark problems and compared with the results from the existing algorithms. The experimental results demonstrate that the proposed algorithm is capable of providing a set of diverse and high-quality non-dominated solutions.