Earticle

초록

영어

This paper proposes an algorithm for the Unrelated Parallel Machine Scheduling Problem(UPMSP) without setup times, aiming to minimize total tardiness. As an NP-hard problem, the UPMSP is hard to get an optimal solution. Consequently, practical scenarios are solved by relying on operator's experiences or simple heuristic approaches. The proposed algorithm has adapted two methods: a policy network method, based on Transformer to compute the correlation between individual jobs and machines, and another method to train the network with a reinforcement learning algorithm based on the REINFORCE with Baseline algorithm. The proposed algorithm was evaluated on randomly generated problems and the results were compared with those obtained using CPLEX, as well as three scheduling algorithms. This paper confirms that the proposed algorithm outperforms the comparison algorithms, as evidenced by the test results.

목차

Abstract
1. 서론
2. 문제 및 수리모형
2.1 문제 설명
2.2 수리모형
3. 기존 일정계획 알고리즘
3.1 우선순위 규칙
3.2 메타휴리스틱 알고리즘
4. 강화학습 기반 일정계획 알고리즘
4.1 강화학습 알고리즘
4.2 정책 네트워크
5. 성능 평가 실험
5.1 실험 방법
5.2 실험 결과
6. 결론
7. References

키워드

저자

• 이태희 [ Tehie Lee | 인천대학교 산업경영공학과 석사 과정 ]
• 김재곤 [ Jae-Gon Kim | 인천대학교 산업경영공학과 ]
• 유우식 [ Woo-Sik Yoo | 인천대학교 산업경영공학과 ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  대한안전경영과학회지 [Journal of Korea Safety Management & Science]

• 간기

  계간

• pISSN

  1229-6783

• eISSN

  2288-1484

• 수록기간

  1999~2025

• 십진분류

  KDC 530 DDC 620