**OPTIMIZATIONS**

Our optimization algorithms span the complex world of supply chain decision making and conquer the domains of customer service, inventory, sourcing, transportation, warehousing, and the supply chain as a whole. A small sample of recent optimizations follows.

Our logistics zone algorithms optimize the assignment of customers to service locations taking into account transportation cost and facility capacities.

Our fill rate optimization computes the fill rate and inventory turn rate that simultaneously maximize the financial and service performance of inventory.

Our delivery frequency algorithm optimizes the times between deliveries or shipments taking into account the implications for transportation, inventory carrying, and lost sales cost. **READ MORE**

Our inventory optimization algorithms work together to computer the turn and fill rate for each SKU that maximizes its financial and service performance.

RightSKUs™ is a multi-criteria algorithm considering critical facets of each SKUs current and forecasted financial, inventory, and service performance. **SEE MORE**

Our forecasting algorithms minimize forecasting errors and dramatically reduce safety stock requirements. **READ MORE**

Our RightStream™, Value Stream Optimization algorithm determines the optimal combination of trading, buying, selling, production, and inventory holding.

Our leadtime optimization algorithms identify offending vendors, part numbers, lanes, and locations and compute optimal leadtimes to minimize inventory and mitigate supply chain risk.

Our fill rate optimization computes the fill rate and inventory turn rate that simultaneously maximize the financial and service performance of inventory.

Our lot sizing optimization determines optimal production run lengths, optimal time between setups, and optimal procurement purchase quantities. **READ MORE**

Our sourcing algorithms minimize the total cost of ownership and supplier risk in identifying the optimal source for each product.

Our lot sizing algorithms determine the optimal purchasing quantities and timing for each SKU taking into account inventory carrying costs and purchase costs.

Our leadtime optimization algorithms identify offending vendors, part numbers, lanes, and locations and compute optimal leadtimes to minimize inventory and mitigate supply chain risk.

Our network optimization algorithms identify the locations that minimize total supply chain costs for some of the world's most complex supply chains. **READ MORE**

Our fleet sizing algorithms determine the optimal number of tractors, trailers, planes, lift trucks, rail cars, vessels, and/or containers required to balance service requirements and investment cost. READ MORE

Our mode mix algorithms minimize the total logistics cost of each and all shipments considering transportation and inventory carrying costs. *READ MORE*

Our delivery frequency algorithm optimizes the times between deliveries or shipments taking into account the implications for transportation, inventory carrying, and lost sales cost.

Our logistics zone algorithms optimize the assignment of customers to service locations taking into account transportation cost and facility capacities.

Our lane depth optimization determines for each SKU the pallet lane depth that maximizes space utilization and minimizes floor storage cost.

Our pallet storage optimization determines the minimum cost storage mode and vehicle for each SKU.

Our broken case picking mode optimization determines the minimum cost storage mode for each SKU; choosing between bin shelving, flow racks, storage drawers, horizontal carousels, vertical carousels, and automated dispensing systems.

Our pick face optimization algorithms are based upon Dr. Frazelle's ground breaking research in the forward-reserve problem. The algorithms determine the pick face size that minimizes the sum of picking replenishment costs for each SKU.

Our pick slot optimization algorithms consider each SKU's popularity, cube movement, percent days picked, and demand correlation in assigning each SKU to it's uniquely optimal location. The solution reduces picking cost, improves picking throughput, reduces picking errors, and improves picking safety.

Our warehouse zoning algorithms consider order construction, demand correlation, and item popularity in constructing optimal warehouse zones that minimize travel time and order picking costs.