• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.78-85
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• 2023

For Multi-UAV systems, a task allocation could be a key factor to determine the capability to perform a task. In this paper, we proposed a task allocation method based on genetic algorithm for minimizing makespan and satisfying various constraints. To obtain the optimal solution of the task allocation problem, a huge calculation effort is necessary. Therefore, a genetic algorithm-based method could be an alternative to get the answer. Many types of UAVs, tasks, and constraints in real worlds are introduced and considered when tasks are assigned. The proposed method can build the task sequence of each UAV and calculate waiting time before beginning tasks related to constraints. After initial task allocation with a genetic algorithm, waiting time is added to satisfy constraints. Multiple numerical simulation results validated the performance of this mission planning method with minimized makespan.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.56-63
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• 2024

As the safety of unmanned vehicles continues to improve, their usage in urban environments, which are full of obstacles such as buildings, is expected to increase. When numerous unmanned vehicles are operated in such environments, an algorithm that takes into account mutual collision avoidance, as well as static and dynamic obstacle avoidance, is necessary. In this paper, we propose an algorithm that handles task assignment and path planning. To efficiently plan paths, we construct a grid-based map and derive the paths from it. To enable quick re-planning in dynamic environments, we focus on reducing computational time. Through simulation, we explain obstacle avoidance and mutual collision avoidance in small-scale problems and confirm their performance by observing the entire mission completion time (Makespan) in large-scale problems.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.305-314
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• 2007

This paper considers single machine scheduling problems where the processing time of a job increases as a function of its position in the sequence. In this model, the later a given job is scheduled in the sequence, the longer its processing time. It is shown that the optimal schedule may be very different from that of the classical version of the problem. We introduce polynomial solutions for the makespan minimization problem, the sum of completion times minimization problem and the sum of earliness penalties minimization problem. For two resource constrained problems, based on the analysis of the problems, the optimal resource allocation methods are presented, respectively.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.135-151
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• 1997

In this paper, we propose a simple and relatively efficient heuristic method to determine job sequencing in the flow-shop considering multiple criteria such as processing time, due date and cost. The proposed method is applicable to the flow- shop where the jobs are released simultaneously and their processing sequence is predetermined and not changed until the whole jobs are processed. To develop this method, we mixed and modified some well-known multi-attribute decision heuristics such as the simple linear weighting scheme, the lexicographic rule and the 'elimination by aspect' rule. Some computer simulations were conducted to test the efficiency of the proposed method and it has been compared with the SWPT (Shortest Working Processing Time) rule and EDD (Earliest Due Date) rule. The results show that our method is as effective as the traditional ones in terms of mean flow time, tardiness, makespan, cycle time, machine utilization, etc., and proved to be much simpler and more flexible to be used in real situations.

• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.129-137
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• 2013

This paper proposed the scheduling method for tire mixing processes using the genetic algorithm. The characteristics of tire mixing process have the manufacturing routing, operation machine and operation time by compound types. Therefore, the production scheduling has to consider characteristics of the tire mixing process. For the reflection of the characteristics, we reviewed tire mixing processes. Also, this paper introduces the genetic algorithm using the crossover and elitist preserving selection strategy. Fitness is measured by the makespan. The proposed genetic algorithm has been implemented and tested with two examples. Experimental results showed that the proposed algorithm is superior to conventional heuristic algorithm.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.81-92
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• 1990

This paper considers a scheduling of a set of jobs on single and multiple processors, when all jobs have a common due date and earliness and lateness are penalized at different cost rates. The objective is to determine the optimal value of a common due date and an optimal scheduling to minimize a total penalty function. It is also shown that a schedule having minimum weighted completion time variances must be V-shaped. For identical processors, a polynomial scheduling algorithm with the secondary objectives of minimizing makespan and machine occupancy is developed and a numerical example is presented.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.3
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• pp.65-77
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• 1994

There are so many situations in which production schedules need to be rescheduled, due to the uncertainty or dynamic characteristics existing in manufacturing environment. Under the circumstances, it is necessary to build a system which helps a schedule manager understand the dynamic situations and reflect his insight into the system easily. We developed a system that can improve a production schedule. The system consists of a schedule editor and a schedule generator. The schedule editor, a rule-based system, always keeps a schedule feasible by keeping track of local changes in the revised one. The schedule generator consists of a two-phase heuristic method. In the lst phase it generates a schedule by a priority rule with Giffler and Thompson algorithm then it improves the performance in terms of the makespan in the 2nd phase. Experimental results show that, most of the times, the system generates a better schedule than the one with ordinary priority rules only.

• IE interfaces
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• v.22 no.1
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• pp.10-16
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• 2009

In this paper, we propose an efficient search algorithm for finding an optimal schedule to minimize makespan, while avoiding deadlock situation in Flexible Manufacturing Systems (FMS) with finite capacity, in which each job needs to be processed in several job stages for completion. The proposed algorithm uses a modeling and control method based on Petri-net. Especially, we improve the efficiency of the search algorithm by using a priority rule and an efficient bounding function during the search procedure. The performance of the proposed algorithm is evaluated through a numerical experiment, showing that it holds considerable promise for providing an optimal solution efficiently comparing to past work.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.231-242
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• 1997

This paper describe an approximation method for solving the minimum makespan problem of job shop scheduling with fuzzy processing time. We consider the multi-part production scheduling problem in a job shop scheduling. The job shop scheduling problem is a complex system and a NP-hard problem. The problem is more complex if the processing time is imprecision. The Fuzzy set theory can be useful in modeling and solving scheduling problems with uncertain processing times. Lee-Li fuzzy number comparison method will be used to compare processing times that evaluated under fuzziness. This study propose heuristic algorithm solving the job shop scheduling problem under fuzzy environment. In This study the proposed algorithm is designed to treat opinions of experts, also can be used to solve a job shop environment under the existence of alternate operations. On the basis of the proposed method, an example is presented.

• Proceedings of the Korean Society for Quality Management Conference
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• 2007.04a
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• pp.491-497
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• 2007

The planning and scheduling is considered as an important function because it influence to the overall performance of production in manufacturing system for supporting global objectives. In this paper, propose the hybrid approach to solve the problem which considered alternative resources and sequences, a sequence-dependent setups and transportation times. The objective of this problem is minimize the makespan with AGV traveling time. A iterative two heuristic algorithm(PSO, SA) is proposed to obtain the sequence of operations and CPLEX package is used to obtain the optimal sub-lot sizes(OLS) when the sequence of operations and greedy-based AGV dispatching rules are fixed or given. we show that performance of iterative two heuristic algorithms and simple numerical experiment.