This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as “makespan”. This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator’s experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

Abstract
1. 서 론
    1.1 서론
    1.2 기존 연구와의 비교
2. 본 론
    2.1 문제 상황
    2.2 수리모형
    2.3 규칙 기반 휴리스틱 알고리즘
    2.4 탐색 기반 휴리스틱 알고리즘
3. 성능 평가 실험
    3.1 실험 방법
    3.2 성능 비교
4. 결 론
5. References

• 이태희(인천대학교 산업경영공학과 석사 과정) | Tehie Lee (Incheon National University Graduate School, Industrial & Management Engineering)
• 유우식(인천대학교 산업경영공학과) | Woo-Sik Yoo (Incheon National University, Dept. of Industrial & Management Engineering) Corresponding Author