• Korean Management Science Review
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• v.30 no.3
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• pp.81-97
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• 2013

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines. Non-identical setup and processing times are assumed for each machine. A genetic algorithm is proposed to minimize the makespan objective measure. In this paper, a lowerbound and some heuristic algorithms are derived and tested through computational experiments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.65-73
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• 2015

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines using GA (Genetic Algorithm). Non-identical setup times, processing times and order lot size are assumed for each machine. The GA is proposed to minimize the total-tardiness objective measure. In this paper, heuristic algorithms including EDD (Earliest Due-Date), SPT (Shortest Processing Time) and LPT (Longest Processing Time) are compared with GA. The effectiveness and suitability of the GA are derived and tested through computational experiments.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.367-381
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• 2011

Reducing waste for the efficiency of production is becoming more important because of the rapidly changing market circumstances and the rising material and oil prices. The dispatching also has to consider the characteristic of production circumstance for the efficiency. The production circumstance has the non-identical parallel machines with rework rate since machines have different capabilities and deterioration levels in the real manufacturing field. This paper proposes a dispatching method, FTLR (Flow Time Loss Index with Rework Rate) for production efficiency. The goal of FTLR is to minimize flow time based on such production environments. FTLR predicts the flow time with rework rate. After assessing dominant position of expected flow time per each machine, FTLR performs dispatching to minimize flow time. Experiments compare various dispatch methods for evaluating FTLR with mean flow time, mean tardiness and max tardiness in queue.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.64-73
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• 2004

This paper addresses a problem of machining determination of input quantity in a multi-stage flexible flow system with non-identical parallel machines considers a subcontracting, machining restraint, and machine yield. We develop a nonlinear programing with the objective of minimizing the sum of in-house processing cost and subcontracting cost. To solve this model, we introduce a single-processor parallel genetic algorithm(SPGA) to improve a weak point for the declined robustness of simple algorithm(SGA). The efficiency of the SPGA is examined in comparison with the SGA for the same problem. In of examination the SPGA is to provide the excellent solution than the solution of the SGA.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.305-312
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• 2014

This research deals with a problem that minimizes makespan in a non-identical parallel machine system with sequence and machine dependent setup times and machine dependent processing times. We first present a new mixed integer programming formulation for the problem, and using this formulation, one can easily find optimal solutions for small problems. However, since the problem is NP-hard and the size of a real problem is large, we propose four heuristic algorithms including genetic algorithm based heuristics to solve the practical big-size problems in a reasonable computational time. To assess the performance of the algorithms, we conduct a computational experiment, from which we found the heuristic algorithms show different performances as the problem characteristics are changed and the simple heuristics show better performances than genetic algorithm based heuristics for the case when the numbers of jobs and/or machines are large.

• Korean Management Science Review
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• v.17 no.2
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• pp.67-73
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• 2000

This paper describes a scheduling support system for a plant where the machine environment may be modeled as non-identical parallel machine lines (NPML). That is, there are a number of stages in series with various different-capability-machines at each stage. Arriving continuously are jobs with their specific due dates, processing times and candidate processing machines. We’ve developed a real-time scheduling module in conjunction with a supporting production information system which supplies necessary data to the module. This scheduling module is one of the 9 modules in this system, and is composed of both a scheduling interface and a production monitoring interface. This module allows users to generate many candidate schedules by selecting their business policies. The selective arguments which are available consist of allocation costs, batch sizes and machine selection intervals. They are now being implemented at a powder metallurgy plant.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.35-41
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• 2003

This paper proposes a heuristic scheduling algorithm to satisfy the customer's due date in the production process under make to order environment. The goal is to achieve the machine scheduling in the transformer winding process, in which consists of parallel machines with different machine performances. The winding is important production process in the transformer manufacturing company. The efficiency of the winding machines is different according to the voltage capacity and the winding type. This paper introduces a heuristic approach in the transformer winding process where the objective function is to minimize the total tardiness of jobs over due dates. The numerical experiment is illustrated to evaluate the performance.

• 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 Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.254-265
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• 1999

We consider two stage hybrid flowshop scheduling problem when there are two non-identical parallel machines at the first stage, and only one machine at the second stage. Several well-known sequence-first allocate-second heuristics are considered first. We then propose an allocate-first sequence-second heuristic to find minimum makespan schedule. The effectiveness of the proposed heuristic algorithm in finding a minimum makespan schedule is empirically evaluated by comparing with easily computable lower bound. The proposed heuristic algorithm as well as the existing heuristics are evaluated by simulation in four cases which have different processing time distribution, and it is found that the proposed algorithm is more effective in every case.

• 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.