## 2 Synchronization Issues with Various Part-to-Picker Systems and a Literature Review
### Synchronization Problems in Hospitals
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Research** & **Article** & **Research Issue** & **Methodology** \\ \hline \multirow{9}{*}{_Category_} & [PERSON]; [PERSON] (2003) & Automated order fulfillment systems & Modeling based on demand levels, labor rates, order sizes, and other factors \\  & [PERSON] et al. (2007) [59] & Vehicle routing problems & General framework [PERSON] a large collection \\  & [PERSON]; [PERSON] (2008) [61] & Warehouse management & Minimize total operation time or maximize the throughput of the cross-docking system \\  & [PERSON]; [PERSON] (2009) [62] & Two-machine cross-docking flow shop & Polynomial approximation algorithm with an error-bound analysis \\  & [PERSON] (2010) [63] & Inbound and outbound trucks at cross-docking terminals & Computerized scheduling and (bounded) dynamic programming \\  & [PERSON] (2010) [64] & Zero-inventory cross-docking terminals & Dynamic programming and heuristic simulated annealing \\  & [PERSON] et al. (2010) & Cross-docking scheduling & Genetic algorithm (GA), particle swarm optimization (PSO), differential evolution (DE), and least significant difference measure \\  & [PERSON] et al. (2013) [68] & Cross-docking terminals with fixed outbound departures & Heuristic-simulated programming (DP) and beam search (BS) for TSPD for linear mixed-integer program (TSFD-MIP) \\  & [PERSON] et al. (2013) [69] & Cross-docking decision support systems & Tabu search \\  & [PERSON]; [PERSON] [PERSON] (2016) & The truck scheduling problem in a cross-docking terminal & Mixed-integer linear programming (MILP) \\  & [PERSON] et al. (2016) [71] & Cross-docking center & Time-indexed mixed-integer linear programming formulation and a polynomial time heuristic \\  & [PERSON]; [PERSON] (2016) & Multiple-door cross-docking systems & Solving the Just-in-time (JIT) problem with ILOG CPLEX solver-based \\  & [PERSON] (2017) [74] & Closed-loop sortation conveyors & Numerical experiments and heuristic simulated to solve the scheduling problem \\ \hline \multirow{9}{*}{_Category_} & [PERSON] et al. (2021) [81] & Automated medicine delivery systems/automated overhead material handling systems & A 3D simulation model in Flexsim (of the queuing model) \\  & [PERSON] et al[PERSON] (2022) [84] & Automated medicine delivery systems/automated overhead material & Redirect products to the correct stations \\  & [PERSON] et al. (2022) [84] & Systems/automated overhead material handling systems & The inventory routing problem (IRP) and the location inventory routing problem (LIRP) \\  & [PERSON] et al. (2023) [85] & [PERSON] et al. (2023) & The inventory routing problem (IRP) and the location inventory routing problem (LIRP) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._This paper also introduced multiobjective path relinking (MORP), a method that dispatchers can use to get solutions with different objective weights in a short computation time. Interactive methods are utilized to realign the process, while criteria aggregation is utilized to add more factors. NP-hard is the cause of the problem. The solution can be achieved by dividing it into three problems: a generalized assignment problem, a multi-mode resource-constrained project scheduling problem (MMRCPSP), and a network flow problem with a convex cost function. More research is required to improve the accuracy of metamodel estimation, such as identifying more influential parameters and preclassifying data. Simulation can be used to access the changing value. By removing arcs and reducing graph complexity, the solution process can be sped up by developing the exact dynamic programming (DP) strategy. The simulation model will need to be more comprehensive as future studies aim to extend to other parts of this system. The focus of cross-docking study should be on generating heuristics with better error boundaries and comparing the model to different objective functions.