Chin-Chia Wu* and Win-Chin Lin

Department of Statistics, Feng Chia University, Taichung, Taiwan, Republic of China

*Corresponding Author: Chin-Chia Wu, Department of Statistics, Feng Chia University, Taichung, Taiwan, Republic of China.

Received: September 02, 2021; Published: October 26, 2021

Some recent hot topics of scheduling problems with great practical value in manufacturing systems and service fields involve designing effective heuristic methods and algorithms to find the best solution for production plans or policies with or without certain constraints. These topics include time-dependent processing times relevant scheduling, and customer order scheduling, etc. According to the literature reviews, it is noted that a lot of studies have been conducted on scheduling theory and its applications to solve different scheduling problems in real-life phonemes for a long time. We can find that researchers pay more attentions on proposing optimal solution searching methods, developing near-optimal heuristics, and discussing computational complexity or on analyzing the behaviors of heuristics (algorithms) according experimenting computational outputs. In classical scheduling model, job processing times are considered as fixed and known integers. However, the learning effect can contribute the job processing times can be further shortened.

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