• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.59
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• pp.37-42
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• 2000

The parallel machines scheduling problems is one of the combinatorial optimization problems that often occurs in the real world. This problem is classified into two cases, one of which is the case which processing time are identical and the other, nonidentical. Not so much researches have been made on the case that nonidentical parallel machines scheduling problem. This study proposes Tabu Search methods for solving parallel machines scheduling problems related to due dates: minimizing mean tardiness, minimizing the number of tardy jobs, minimizing the maximum tardiness.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.37-50
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• 1998

This paper considers the nonidentical parallel machine scheduling problem in which n jobs having different due dates are to be scheduled on m nonidentical parallel machines. For the make-to-order manufacturing environment, the objective is to minimize the number of tardy jobs. A 0-1 nonlinear programming model is formulated and a heuristic algorithm that allocates and sequences jobs to machines is developed. The proposed algorithm makes use of the concept of assignment problem based on the suitability measure as the cost coefficient. Computational experiments show that the proposed algorithm is superior to the existing one in some performance measures such as number of tardy jobs. In addition, this algorithm is appropriate for solving real industrial problems efficiently.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.329-338
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• 2007

This paper presents a dispatching algorithm for nonidentical parallel machines problem considering rework, sequence dependent setup times and release times. For each pair of a machine and a job type, rework probability of each job on a machine can be known through historical data acquisition. The heuristic scheduling scheme named by EDDR (Earliest Due Date with Rework probability) algorithm is proposed in this paper making use of the rework probability. The proposed dispatching algorithm is measured by two objective function value: 1) total tardiness and 2) the number of reworked jobs, respectively. The extensive computational results show that the proposed algorithm gives very efficient schedules superior to the existing dispatching algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.59-59
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• 1997

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.60
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• pp.67-72
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• 2000

In this paper we consider to parallel machines scheduling problems for minimizing mean tardiness that is known NP-complete. This problems is classified into two cases, one of which is the case which processing time are identical and the other, nonidentical. A Tabu Search method is applied to the problems considered in this paper to get an improved solution. To this end, we design move attribute, Tabu attribute and Tabu tenure, and thereafter perform the experiments to the problems.

• 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 Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.41-52
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• 1999

In this paper, a load balancing problem among operators is considered, when one or more machines can be assigned to an operator. The machines are grouped into two types and there are more than one machines in each group. The type of machine in which a job can be processed, is determined. However, an operator can handle both types of machine. The elementary operations of a job are classified into three classes : machine-controlled elements, operator-controlled elements and machine/operator- controlled elements. The objective is to balance the workloads among operators under the constraints of available machine-time and operator-time. A heuristic solution procedure is suggested for allocating jobs to machines and allocating machines to operators. The performance of the algorithm is evaluated with various data set.

• 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.