Abstract: A computer-implemented method for managing a supply chain including a central distribution center (DC) that distributes products to one or more edge DCs. The method may include determining, by one or more processors, a first rate of change of future demand for a product distributed by the edge DC over a predetermined future time horizon, and a second rate of change of historical demand for the product distributed by the edge DC over a historical time period. The method may also include updating flow of customer orders and storage space requirements for the central DC and the edge DC based on a difference between the first rate and the second rate.

Abstract: A computer-implemented method for managing a supply chain including a plurality of supply chain entities is disclosed. The method may include determining a plurality of input parameters for modeling the supply chain. Each input parameter has a plurality of input parameter values within a plausible range. The method may also include determining a plurality of candidate network structures, and determining a business goal value for each candidate network structure based on a plurality of possible input combinations of the input parameter values. The method may further include determining a statistical distribution of the business goal values for each network structure.

Abstract: A method for managing a logistics network is disclosed. The method may include receiving, by a processor, historical demand data representing historical demand for an item at each one of a plurality of facilities associated with the logistics network, the plurality of facilities including at least one manufacturing facility and at least one distributing facility; forecasting future demand data representing a forecasted future demand for the item at each one of the plurality of facilities based on the respective historical demand data and one or more respective business goals for each facility; adjusting the future demand data at each one of the facilities by compensating for a shipping time delay associated with shipping the item from a supplier to the facility; and combining the adjusted future demand data at each one of the facilities to generate combined future demand data representing demand for the item at the supplier.

Abstract: A computer-implemented method for forecasting characteristics of a target item is disclosed. The method may include determining a forecast function representing characteristics of the target item. The forecast function may include one or more generic functions and one or more customer-specific functions. Each one of the generic functions may be uniform for a plurality of customers within one or more customer groups and may have one or more generic function variables. Each one of the customer-specific functions may be specifically configured for a corresponding customer group and may have one or more customer-specific function variables. The method may also include determining a data value for each one of the generic function variables and the customer-specific function variables by using a genetic algorithm. The method may further include forecasting the characteristics of the target item by using the forecast function and the determined data values.

Abstract: A computer-implemented method for automatically communicating updates between a computer-aided-design (CAD) module that generates a representation of the physical structure of a facility and a discrete event simulator (DES) module that simulates processes occurring within the facility is disclosed. The method may include establishing a communication link between the CAD module and the DES module.

Abstract: A computer-implemented method for simulating movement of materials within a facility using predefined software objects is disclosed. The method includes storing a plurality of predefined software objects in a computer memory, each of the predefined software objects including one or more discrete event simulator commands and representing a process performed at a facility. The method also includes receiving, by one or more processors, an instruction to simulate movement of a material within a facility, and linking, by the one or more processors, two or more of the predefined software objects together to represent the movement of the material within the facility. The method further includes executing, by the one or more processors, the linked predefined software objects using a discrete event simulator to simulate the movement of the material within the facility.

Abstract: A computer-implemented method for processing order information is disclosed. The method includes receiving operational guidelines for controlling workflow of resources at a facility and receiving, by one or more computer processors, order information including a plurality of orders. The method also includes generating, by the one or more computer processors, discrete event simulator commands for fulfilling the orders by applying the operational guidelines to the order information, and simulating the workflow of the resources within the facility to fulfill the orders by executing the discrete event simulator commands.

Abstract: A computer-implemented method for simulating a facility to achieve one or more business goals is disclosed. The method includes receiving, by a processor, one or more input parameters for a discrete event simulator (DES) module for a facility, a plurality of business goals for the facility, and a selection of a goal optimization technique. The method also includes generating, by the processor, a DES output that simulates processes occurring within the facility based on the one or more input parameters and simultaneously achieves the business goals in accordance with the selected goal optimization technique.