In practice, stock market behavior is difficult to predict accurately because of its high
volatility. To improve market forecasts, a method inspired by Elman neural network and …

In general, customers are looking to receive their orders in the fastest time possible and to
make purchases at a reasonable price. Consequently, the importance of having an optimal …

In order to handle incomplete, ambiguous, and inconsistent data, the concept of a
neutrosophic set (NS) has gained immense popularity. Due to its independent …

This paper provides an integrated model for a two-stage assembly flow shop scheduling
problem and distribution through vehicle routing in a soft time window. So, a mixed-integer …

This paper investigates a flexible flow shop scheduling problem wherein there are some
unrelated parallel machines with different technology levels in the first stage. Some of these …

As the most crucial component of a hospital, the operating room (OR) is the primary source
of revenue generation and expenditures. The hospital's overall performance will be …

The presented study proposes a novel bi-objective mixed integer linear programming (MILP)
framework for the multi-mode resource-constrained project scheduling problem (MRCPSP) …

This paper addresses the economic lot and delivery scheduling problem (ELDSP) within
three-echelon supply chains, focusing on the complexities of demand uncertainty, limited …

Abstract The Multi-Trip Multi-Compartment Vehicle Routing Problem with Backhauls
(MTMCVRPB) is a complex optimization problem that involves finding the most efficient …

This paper addresses machines and automated guided vehicles (AGVs) simultaneous
scheduling with alternative machines in a multi-machine flexible manufacturing system …