# A Review of the High-Mix, Low-Volume Manufacturing Industry
## 5 Models and Algorithms for HMLV Scheduling
### Type of Common Modelling and Simulation Methods
#### 5.4.2 Discrete-Event Simulation  
DESs were the common methodology to simulate the HMLV production system. Table 5 shows some of the specific software being noted.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Genetic Algorithm** & \\ \hline [PERSON] et al. (2010) [49] & Material allocation \\ [PERSON] et al. (2010) [85] & Product mix optimisation—GA based TOC; particle swarm optimisation; layered-encoding cascade optimisation \\ [PERSON] and [PERSON] (2012) [86] & Dispatching policy \\ [PERSON] et al. (2013) [87] & Levelling with group technology—non-dominated sorting \\ [PERSON] et al. (2014) [88] & Job allocation—resource-constrained project scheduling \\  & problems (RCPSPs) \\ [PERSON] et al. (2014) [78] & Demand forecasting \\ [PERSON] et al. (2018) [60] & Order allocation to MTO production sites \\ \hline \hline
**Linear Programming** & \\ \hline [PERSON] and [PERSON] (2013) [73] & LP for maximum molten alloy usage—die cast scheduling \\ [PERSON] et al. (2017) [69] & Optimal schedule for transient processes—RPA scheduling \\ [PERSON] and [PERSON] (2020) [40] & Machine distance algorithm—robotic layout \\ \hline \hline
**Reinforced Learning** & \\ \hline [PERSON] et al. (2020) [89] & Deep learning with transfer approach—dispatching policy \\ [PERSON] and [PERSON] (2022) [90] & Predictive maintenance decision model—Markov chain model \\  & with dynamic programming \\ [PERSON] et al. (2022) [91] & Online scheduling for decision making—Markov decision \\  & process (MDP) \\ \hline \hline \end{tabular}
\end{table}
Table 4: _Cont._  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Discrete-Event Simulation** & \\ \hline [PERSON] et al. (2011) [92] & Factory modelling for PCBA \\ [PERSON] et al. (2012) [42] & Order fulfilment based on virtual time-based flow principle \\ [PERSON] et al. (2019) [79] & Simulation-based decision support \\ [PERSON] and [PERSON] (2019) [43] & Setting CONWIP limit \\ [PERSON] et al. (2019) [93] & Visualisation of simulation on VR \\ [PERSON] and [PERSON] (2021) [94] & Backward scheduling \\ \hline \hline WITNESS & \\ \hline [PERSON] (2011) [95] & Linking database with witness for scheduling \\ [PERSON] et al. (2015) [18] & POLCA authorisation simulation \\ [PERSON] et al. (2019) [50] & Energy consumption based on lot-size optimisation \\ \hline ARENA & \\ \hline [PERSON] and [PERSON] (2009) [58] & Order fulfilment model based on customer’s flexibility \\ [PERSON] et al. (2019) [46] & POLCA—centralised vs decentralised job release \\ [PERSON] et al. (2021) [96] & Modelling right—temporal consolidation for MTO \\  & supply chain \\ \hline \hline AnyLogic & \\ \hline [PERSON] and [PERSON] (2011) [97] & Fab simulation model \\ \hline SimPy & \\ \hline [PERSON] et al. (2020) [12] & WLC assessment in additive manufacturing ORR \\ \hline FlexSim & \\ \hline [PERSON] et al. (2022) [98] & Production modelling of manual or semi-automated \\ assembly lines & \\ \hline \hline \end{tabular}
\end{table}
Table 5: List of DES-related work and their objectives.