Basic Optimization Training

Basic Optimization Training
LLamasoft, Inc October 2008

Optimization Course Overview
Course Goal: Understand the basics of supply chain optimization through lecture, computer exercises, and coaching Course Objective: Students will be able to use the software, with minimal assistance, to correctly build a supply chain model; add the basic components of optimization to the model; perform an optimization; interpret the results through outputs; and perform an infeasibility analysis.

Overview of Model Components Optimization Basic Components
Agenda Overview of Model Components Optimization Basic Components Structure Cost Constraints Infeasibility Analysis Optimization Results Review

Model and Optimization Overview

Model Elements

Understanding Optimization
What is the optimal network structure? Thousands of possibilities… Evaluate millions of alternatives, find the global optimal structure: lowest cost structure that meets the constraints Determine the optimal supply chain network structure using MIP/LP programming …One Optimal Answer!

Optimization Basic Component 1
Structure

Learning Objective- Structure
Explain the basic components to modeling in the software Use the components to create a supply chain network Perform a network optimization Goal: Successfully design a new optimal supply chain network using the software

Example Network Design- Sites
FW1 FW2 FW3 FW4 FW5 P1 P2 P3 PW1 PW2 PW3 S1 S2 CZ1 CZ5 CZ6 CZ2 CZ3 CZ4

6 Essential Elements in Models
Structure 6 Essential Elements in Models Sites Products Demand Sourcing Policies Transportation Policies Inventory Policies

Exercise 1: Network Optimization

C://Llamasoft/Training/Optimization
Model Folder Go to Computer and Create Folder: C://Llamasoft/Training/Optimization

Open Supply Chain Guru Start

Add a New Model Go to File  Add A New Model

Saving Models and Projects
Save Model in Training Folder: C://Llamasoft/Training/Optimization Save Model As: Opt_Training_Basic Save Project As: Guru_Training

Site Types Customer Site Only customer sites can have demand
Customer sites have sourcing policies but NO inventory policies They do not ship to other sites or produce any products Flow into customer sites = $$$ (revenue!) Existing Facility Indicates this site presently exists in the supply chain Potential Facility Indicates this site presently does not exist in the supply chain Type, and Choice combine to determine which costs to apply Open Potential Facility = Add Startup Cost Closing Existing Facility = Add Closing Cost Always incur Fixed Operating Costs if flow exists

Creating the Opt_Training_Basic Model
4 Sites IP MFG DC 1 CZ DC 2 IP SP SP TP TP IP SP SP TP TP 2 Products Product A Product B

Opt_Training_Basic Model: Sites
CZ DC 1 MFG DC 2 Name Location (Address, City, State, Country, Postal Code, Latitude, Longitude) Capacity Period, Capacity Basis Fixed Startup Cost/Cap, Fixed Operating Cost/Cap Closing Cost

Opt_Training_Basic Model: Add Customer Site
Open the Sites Table Add Customer Site Name: CZ City: New York State: New York Type: Customer Graphic: Circle Graphic Color: Green Leave all other fields default

Opt_Training_Basic Model: Add DCs
Add Distribution Center 1: Name: DC_1 City: Omaha State: Nebraska Type: Existing Facility Graphic: Triangle Graphic Color: Yellow Add Distribution Center 2: Name: DC_2 City: Austin State: Texas Type: Existing Facility Graphic: Triangle Graphic Color: Yellow

Opt_Training_Basic Model: Add Manufacturer
Name: MFG City: Los Angeles State: California Type: Existing Facility Graphic: Square Graphic Color: Red

Opt_Training_Basic Model: Column Update
Place cursor in the Graphic Size Field Right Click or Select the Column Update Button on the toolbar Select 10 from the drop down menu and apply the update

Opt_Training_Basic Model: Layout Map
Display the Sites on the Layout Map

Opt_Training_Basic Model: Products
Product A Product B Name/ SKU Inventory Valuation Price Weight, Cubic Status

Opt_Training_Basic Model: Add Products
Open the Products Table Add (2) Product Records Product_A Value: 5 Price: 10 Weight: 5 Cubic: 5 Status: Include Product_B Value: 10 Price: 20 Weight: 10 Cubic: 10 Status: Include

Opt_Training_Basic Model: Demand
Customer Site Product Quantity Occurrences Time Between Orders Due Date Price

Opt_Training_Basic Model: Add Demand
Open the Demand Table Add (2) Demand Records Record 1 Customer Site: CZ Product Name: Product_A Quantity: 100 Order Time: 0 Record 2 Customer Site: CZ Product Name: Product_B Quantity: 100 Order Time: 0

Shipments Vs. Demand Shipments are typically modeled through the Transportation Policies table Shipments table allows you to model shipments outside of the Transportation Policies table There are no cost fields in the Shipments data table- the costs in the Transportation Policies table are used to calculate the transportation costs Allows for accurate modeling of a “Push” system, instead of a demand driven supply chain

Opt_Training_Basic Model: Sourcing Policy
MFG DC 1 CZ DC 2 Product_A, Product_B Identifies which sites to send replenishment and customer orders, and whether product is ordered from an outside source or made at that site

Types of Sourcing Policies
Single Source Single Source (Select Closest) Multiple Sources (Most Inventory) Multiple Sources (Order of Preference) Multiple Sources (Probability) Source by Transfer Make Make by Schedule Make (Single Process) Make (Order of Preference) Make (Probability) Hint: Use the Quick Reference Card for descriptions of these policies!

Opt_Training_Basic Model: Adding Sourcing Policies
Open the Sourcing Policies Table Add a total of (10) Sourcing Policies 4 Multiple Sources (Most Inventory) CZ can source Product_A from DC_1 and DC_2 CZ can source Product_B from DC_1 and DC_2 4 Single Source Each DC can only source from the MFG for Both Products 2 Make 1 for each product at the Manufacturer

Opt_Training_Basic Model: Layout Map
Display the Sourcing Policies on the Map

Opt_Training_Basic Model: Transportation Policy
MFG DC 1 CZ DC 2 There must be at least one Transportation Policy that applies to source and destination which is not “Make” Each Transportation Policy defines a “Flow” Source Site Destination Site Product (all applicable products if not explicitly entered) Mode (1 if not explicitly entered)

Types of Transportation Policies
Parcel LTL (Less than Truckload) Full TL (Full Truckload) Air, Rail and Ship Daily or Weekly Shipment Periodic Shipment Pooled Outbound/ Pooled Inbound Pooled Periodic Outbound/ Pooled Periodic Inbound Flow (Optimization Only) Link To Lane Aggregate Container Disaggregate Container

Opt_Training_Basic Model: Add Transportation Policies
Open the Transportation Policies Table Add (4) Transportation Policies One for each Source-Destination combination defined in the Sourcing Policies Source Sites: MFG, DC_1, DC_2 Destination Sites: DC_1, DC_2, CZ Leave all other fields at default value

Opt_Training_Basic Model: Inventory Policy
DC 1 DC 2 MFG Product_A Product_B Defines Initial Inventory Levels Safety/ Cycle Stock Levels Associated Costs One Inventory Policy is optional for each product at the facility sites

Opt_Training_Basic Model: Add Inventory Policies
Open the Inventory Policies Table Add (6) Inventory Policies One for each Facility (non-Customer Site) and Product combination Sites: MFG, DC_1, DC_2 Product Name: Product_A, Product_B Leave all other fields at default value

Opt_Training_Basic Model: Add Costs
Open the Sourcing Policies Table Add a sourcing cost to one lane (2 policies) Use the filter bar to view only DC_1 Update the Average Unit Cost to 1 and clear the filter How do you think this will affect the optimization results?

Opt_Training_Basic Model: Model Options
Go to Tools Model Options (F3) Review Optimization Period Start Date / Time End Date / Time

Opt_Training_Basic Model: Run the Optimization
Optimize the Supply Chain Save the Project and the Model

Opt_Training_Basic Model: Optimization Solver
View Optimization Results Optimization Output Tables Metrics Graphs Auto Implement Optimized Network

Check on Learning- Structure
You should be able to: Open Supply Chain GuruTM Add a new model Save a project Save a model Open a table Understand differences between sites and customers Use the filter bar Move from field to field Open the layout map Change settings on the layout map View sites and policies on the layout map Understand the types of Sourcing policies Understand the types of Transportation Policies Understand when to use shipments vs demand Understand the types of Inventory Policies Enter data into tables Access the help system Set Optimization Options Run a simple optimization Run the error check on a model Access Optimization Outputs

Costs

Learning Objective- Cost
Distinguish between the different costs used in Supply Chain Optimization with the software Apply costs to the network built in Exercise 1 Goal: Successfully optimize the network with the new costs included

Three Basic Components of Optimization
Structure Costs Constraints

Basic Costs for Optimization
Site Costs Fixed operating Fixed startup Closing Transportation Costs Average Cost Duty Rate Discount Rate Return Trip Cost Transportation Asset Costs Unit Fixed Cost Inventory Costs Site inventory In-transit inventory Inbound and Outbound Warehousing Production Costs Work Center Costs Fixed Operating Fixed Startup Closing Work Resource Cost

Basic Costs Site Costs

Site Costs Fixed Operating Fixed Startup Closing

Site Costs: Fixed Operating
Costs associated with the day to day operations of the facility Enable use of a step- function to associate the operating cost based upon operating capacity

Site Costs: Fixed Operating
Facility is closed/not used if the throughput is zero. Facility is open at Level 1 if the throughput is between 0 and 5,000 pounds. Facility is open at level 2 if throughput greater than 5,000 pounds

Site Costs: Fixed Start-Up
Costs to open and begin operating a new facility Only applies to Potential Facilities No thoughput constraints Ability to use step- function to associate start up cost with operating capacity

Site Costs: Closing Cost to end operations at an Existing Facility
Does not apply to Potential Facilities or Customers

Exercise 2a: Add Site Costs

Exercise 2a: Create New Cost Model
From the Project Explorer, right click on the Opt_Training_Basic Model Select Copy Model Right Click on the copied model Select Save Model As Save model as: Opt_Training_Cost

Exercise 2a: Add Fixed Operating Costs
Open the Sites Table Open the Field Guru Enter the following Fixed Costs: DC_1 Capacity Cost DC_2 Capacity Cost 0 50

Exercise 2a: Complete Fixed Operating Costs
Now run the optimization and view the results!

Basic Costs Transportation Costs

Transportation Costs: The Concept of “Flow”
In Optimization, there are no individual shipments Instead it is the total amount shipped, as determined by the optimizer This total amount is the “Flow”. Site A Site B 10,000 Units

Transportation Cost “Average Unit Transportation Cost” Average Cost
Cost Basis Shipment Weight Distance

Transportation Cost: Average Cost
Related to Cost Basis Transportation Cost per Cost Basis Unit Associated Field Guru

Transportation Cost: Cost Basis
Weight = Avg Cost * Weight of Flow Qty = Avg Cost * Number of Units of Flow Cubic = Avg Cost * Volume of Flow Distance = Cost per Mile Fixed = Fixed Cost per Shipment Weight-Distance = Cost per Pound per Mile Qty-Distance = Cost per Unit per Mile Cubic-Distance = Cost per Volume per Mile

Transportation Cost: Distance and Fixed Cost Basis
In order to cost these correctly the optimizer needs to approximate the number of shipments made Site A Site B 10,000 Units Total Flow

Transportation Cost: Shipment Weight
Since the optimizer only knows the flow (sum of all shipments), the only way to cost at the “shipment” level is to approximate the shipment size. If the flow is 10,000 pounds, and the average shipment weight is 1000 pounds that corresponds to 10 shipments.

Transportation Cost: Distance
Calculate using Straight Line Based on latitude and longitude of source and destination sites Adds a circuity factor (17%- in Model Options) Calculate Using Mappoint Routing Interfaces with Microsoft Mappoint to determine actual road distance Must have Map Point installed on the same computer

Transportation Cost: Transportation Assets
Total cost of owning or using each unit of this asset This is a fixed cost, not used to calculate profits or expenses in the network operation Included on the summary report, can be used to compare various scenarios

Transportation Cost: Other Costs
Duty Discount Rate Return Trip Cost

Exercise 2b: Add Transportation Costs to Cost Model

Exercise 2b: Add Transportation Costs
Copy Opt_Training_Cost Model Save as Opt_Training_Cost_Transpo Add the following costs: MFG facility always costs 2.00 per unit shipped to any location DC_1 costs per unit, per mile to ship to the customer DC_2 costs per unit, per mile to ship to the customer

Exercise 2b: Results Now run the optimization and view results!

Basic Costs Inventory Costs

Inventory Costs Facility Inventory Holding
In-transit Inventory Holding Inbound Warehousing Outbound Warehousing

Inventory Costs: Facility Inventory Holding
Inv Holding Cost = Avg Inv * Product Value * (i/365) * T Avg Inv = Average Inventory Product Value = Value in Products Table i = Annual inventory carrying cost % T = Optimization period in days

Inventory Costs: Average Inventory Calculation
Method of Calculation Inventory Turns OR Constituent Parts Safety Stock Inventory Cycle Stock Inventory Pre-Build Inventory

Facility Inventory Level Determination
Factors which affect inventory levels Volume/ Qty of product throughput (Tput) Number of facilities in the network As the number of facilities decreases, the average inventory in the remaining facilities increases due to increased throughput, but at a decreasing rate. Total Facility Inventory

Average Inventory Calculation 1: Inventory Turns
Ratio of inventory throughput to average inventory Increasing Inventory Turns reduces Facility Holding Costs Must balance turnover with safety stock to avoid stockout Also called Stock turns, turns, stock turnover

Inventory Turns: Linear Approximation
Inv Turns = 8 Avg Inv = m * Tput m = Inverse of Inventory Turns Tput = Volume of Product Throughput

Inventory Turns: Pooling Effect
Piecewise linear approximation Used in locations with considerable amounts of product, typically called a distribution center Average Inventory can defined over multiple ranges of throughput. Format for the relationship is a series of pairs <lower range value, turns value> Piecewise linear functions are usually only used at DCs and other locations where considerable product is held. Other locations which hold less inventory tend to exhibit liner holding costs for most products- Modeling the Supply Chain, 2nd Ed. Shapiro, Jeremy. Page 417

Average Inventory Calculation 2: Constituent Parts
Pre-build Safety Stock Cycle Stock

Constituent Parts: Pre-Build Inventory
Results from demand exceeding production capability in one period, but excess production completed in the previous period Example In a 2 period model MFG has a production capacity of 50 units The demand is 20 and 80 units in Periods 1 and 2 respectively The MFG site produces 50 units each period In the first period the 30 excess units produced are stored as Pre-Build Inventory Viewed in the Optimization Output- Inventory Table

Constituent Parts: Safety Stock
Held excess product Also called a buffer The model may tap into the safety stock when necessary

Constituent Parts: Cycle Stock
Portion of inventory allocated to meet anticipated demand In a simple model where demand is constant, cycle stock equals half the order size The blue line refers to actual cycle inventory The red line refers to the average cycle stock The order size is 2 units and occurs once per unit time

Average Inventory Calculation: Constituent Parts
Sum of pre-build inventory, safety stock and the cycle stock

Inventory Costs: Facility Inventory Holding
Why determine Average Inventory? Avg Inv is used to calculate Facility Inventory Holding Costs in the Optimization Inv Holding Cost = Avg Inv * Product Value * (i/365) * T Avg Inv = Average Inventory Product Value = The Product’s Value in the Products Table i = Annual inventory holding cost % T = Optimization period in days

Inventory Costs: In-transit Inventory
Total Cost due to value of products being transported and transport time In-transit Inventory Cost = Q * Product Value * (i/365) * T Q = Quantity of Products in-transit Product Value = Value in Products Table i = Capacity Cost % in Model Options T = Transport Time in Days

In-transit Inventory Costs: Example
Customer Demand = 1000 units 10 days 90 days DC_B_Overseas DC_A_Local Product Value = $500 In-transit Inventory Cost = Q * Product Value * (i/365) * T A to C  1000 * $500 * (15%/365) * 10 = $2,055 B to C  * $500 * (15%/365) * 90 = $18,493

Inventory Costs: Inbound and Outbound Warehousing
Inbound Warehousing Cost: activity cost of handling and moving one unit of product from receiving dock to inventory Outbound Warehousing Cost: activity cost of removing one unit of this product from inventory to the shipping dock Includes such costs as paper tracking procedures, handling equipment, and personnel Does not include Transportation Costs

Exercise 2c: Add Inventory Costs

Exercise 2c: Add Inventory Costs
Copy Opt_Training_Costs_Transpo Save as Opt_Training_Costs_Inventory DC_1 5 Inventory Turns 15% Annual Inventory Holding Cost Inbound Warehousing= .5 Outbound Warehousing = .6 DC_2 7 Inventory Turns 15% Annual Inventory Holding Cost Inbound Warehousing = .7 Outbound Warehousing = .8

Exercise 2c: Results Run the Optimization and View the Results!

Basic Costs Production Costs

Work Center Costs (Sub Models)
Production Costs Simple Costing Work Center Costs (Sub Models) Fixed Operating Fixed Startup Closing Work Resource Costs

Production Costs: Simple Unit Production
Avg Unit Cost field for a “Make” sourcing policy Source Name field is left blank. Field Guru enables costing from a Step Graph for Economies of Scale

Constraints

Learning Objective- Constraints
The learner will be able to explain the different constraints involved in the software, identify potential constraints to a supply chain model, apply constraints to a practice model, and successfully perform an optimization on the model

Constraints in Optimization
Basics of Constraints Aggregate Constraints Flow Inventory Production Site Service Constraints Max Sourcing Distance Due Date End to End Bundled Demand

The Basics of Constraints: Definition
Restrictions placed upon the model Aggregate Constraints: restriction defined for a sum over multiple objects, with at least one object having two or more values Flow Inventory Production Site Service Constraints: restriction placed on the service to a customer

The Basics of Constraints: Use in the Software
Types of Constraints Minimum Maximum Fixed Conditional Minimum Constraint Variable Inputs Specific: Refers to one site/ product/ time period/ mode Set: Refers to a group of sites/ products/time periods/ modes All: Refers to all sites/ products/ time periods/ modes

Aggregate Constraints
Throughput Flow Inventory Production Site

Aggregate Constraints: Throughput
Site is restricted by the amount of flow (basis)in the model during the specified period Step function depicts capacity limit with INF

Aggregate Constraints: Flow
Flow requirement, flow requirement type, flow requirement basis, and time period that the restriction occurs Restricted by 5 elements: Site, Destination, Mode, Product , or Time Period DC 1 CZ 1

Aggregate Constraints: Flow
Places a restriction on the product flow over a set of time periods, between source and destination sites, for products or when using a specified mode

Aggregate Constraints: Flow Count
Sets up intricate constraints in the model linking the following 5 variables; Source, Destination, Product, Mode and Period By aggregating the Destination Sites, Products and Modes it disregards the various possible flows that are due to these variables

Aggregate Constraints: Inventory
Restricted by 3 Elements Site Product Time Period

Aggregate Constraints: Inventory
Allows the specification of additional rules regarding inventory Defines aggregated quantities over sites, products, and time periods

Aggregate Constraints: Inventory Count
Similar to aggregate flow count Can utilize the “Set” feature of the Groups Table

Aggregate Constraints: Production
Restricted by 4 elements Site Process Product Time Period

Aggregate Constraints: Production
Defines aggregated productions that need to be restricted by a plant, or set of plants and by products, or set of products

Aggregate Constraints: Production Count
Similar to Aggregate Flow Count, but pertains to Productions

Aggregate Constraints: Site
Defines the minimum and maximum number of open sites allowed in a set of periods

Aggregate Constraints at Sites
Allows the user to customize the number of sites that can be used in a specific time period

Service Constraints Maximum Sourcing Distance Due Date End to End Bundled Demand

Service Constraints: Maximum Sourcing Distance
Consider a network with manufacturing, warehousing, and customer echelons. All flows between two successive echelons are permitted. DISTANCES M2 M3 M1 CZ_1 CZ_2 CZ_3 CZ_4 WH2 WH3 WH1 WH1 WH2 WH3 M1 500 800 120 M2 600 1000 200 M3 300 750 CZ_1 CZ_2 CZ_3 CZ_4 WH1 180 720 340 600 WH2 700 150 280 100 WH3 200 70 640

Maximum Sourcing Distance
If the maximum sourcing distance is 200 miles for customers and 500 for the warehouses, the network is reduced to the following flow alternatives. DISTANCES CZ_1 WH1 WH2 WH3 M1 500 800 120 M2 600 1000 200 M3 300 750 M1 WH1 CZ_2 M2 WH2 CZ_3 CZ_1 CZ_2 CZ_3 CZ_4 WH1 180 720 340 600 WH2 700 150 280 100 WH3 200 70 640 M3 WH3 CZ_4

Maximum Sourcing Distance
Between the end site and the source node Distance Based Can be set in either the Sourcing Policy Table or the Service Requirements Table

Service Constraints: Customer Due Date
Customer due date-driven service constraints force the demand to be classified by customer lead times. Suppose P1 demand at each customer is 100 units. Classified demand CZ_1 CZ_2 CZ_3 WH2 WH1 P1 in 7 days=75 P1 in 3 days=25 P1 in 5 days=50 P1 in 1 days=50 P1 in 6 days=40 P1 in 5 days=60 4 3 2 6 5 7 1 Air Truck Rail

Customer Due Date All supply alternatives are feasible for the first demand classification, but only the following alternatives are feasible for the second classification CZ_1 CZ_2 CZ_3 WH2 WH1 P1 in 3 days P1 in 1 days P1 in 5 days 4 2 5 3 1 Air Truck Rail

Customer Due Date Only from the last echelon site to the customer
Time- based Set in the Demand Table

Service Constraints: End-to-End
End-to-end service requirements are given from a make-node to a customer node. M2 M1 CZ_1 CZ_2 WH2 WH3 WH1 Time from M1 to CZ_1 for Product1 <= 5 days Time from M2 to CZ_1 for all products <= 7 days Distance from M1 to CZ_2 for Product2 <= 250 miles

End to End Constraints Source Site does not have to directly deliver to the customer; there may be other facilities in the network where the order will pass through Specified by maximum time for an order to leave the facility and reach the customer OR by maximum allowable distance between the facility and the customer Set in Service Requirements Table

Service Constraints: Bundle Demand
When choosing to bundle demand, demand for all products at one customer site will be sourced from one or multiple facilities at the same ratio WH1 450 75 Demand CZ_1(P1) = 600 Demand CZ_1(P2) = 100 CZ_1 150 25 WH2

Bundled Demand Check this box to aggregate all the demand by customers
When a customer demands multiple products, these are sourced in equal ratios from one or multiple sites (proportional to the demand quantities for these products)

Exercise 3a: Constraining the Optimization Model

Unconstrained Model Al Five DCs in Use
Houston Processing Plant supplies only DC_KC

With Aggregate Flow Constraints
Max Flow Reqt Type means at most 500 units of flow can go through DC_Albany. Cond Min Flow Reqt Type means we either have at least 1000 units flow through DC_Portland or none at all. How does this change our optimized results?

With Aggregate Flow Constraints
DC_Portland not used, customers now served by DC_Phoenix Fewer CZs in Northeast are served by DC_Albany, more by DC_Atlanta

With Aggregate Production Constraints
Max Flow Requirement Type means that at most 1000 units can be produced at Norfolk. Min Flow Requirement Type means at least 850 units must be produced at Reno. How does this change our optimized results?

With Aggregate Production Constraints
Fewer CZs in Midwest served by DC_Atlanta, more by DC_KC.

With Aggregate Site Constraints
Create Group that contains all five DCs. Constrain Optimizer to select between one and three sites from within that group. How does this change our optimized results?

With Aggregate Site Constraints
Portland and Phoenix DCs are unused, KC picks up the slack.

With Aggregate Inventory Constraints
Open the Optimization Output Inventory table and note the inventory costs at DC_KC. Set Minimum Inventory at DC_KC to 100 units. Optimize the model. How does this change inventory costs at DC_KC?

Exercise 3b: Add Constraints

Exercise 3b: Add Constraints
Copy the Final Cost Model Save as Opt_Training_Constraints Add the following Constraint: DC_1 can only ship a maximum of 50 units of Product_A to CZ_1 for the entire model period (Horizon) Now run the model and view the results! How this affect the network design?

Check on Learning- Constraints
You should be able to: Define aggregate constraints Define service constraints Open the service requirements table Open the aggregate constraint tables Create service constraints Create aggregate constraints Define and distinguish between serve and aggregate constraints Explain the constraint requirement types Apply aggregate constraints to a model Apply service constraints to a model Understand aggregate constraints sum and objects

Infeasibility Analysis

Guru Infeasibility Analysis
Sometimes the optimization solver returns with a “Problem Infeasible” error message Infeasibility refers to a problem with input data- there is no solution that fulfills all the constraints Guru provides the following tools to help the user identify the source of infeasibility Check for supply-demand imbalance Check for logic errors in defining the network structure Remove all or some hard constraints and solve again

Infeasibility Analysis
Select the hard constraints to impose

Optimization Results

Optimization Results Output Tables Graphs Metrics Layout Map Comparing Models

Optimization Results: Output Tables
Summary Network Customer Facility Work Center Transportation Asset Work Resource Flows InterFacility Production Process Details Productions Inventory Aggregated Demand

Optimization Results: Graphs
Click of button to display results Numerous choices for data display

Optimization Results: Metrics
Quick access to outputs Tables can be exported to Excel

Exercise 4: View Optimization Outputs

Viewing Optimization Outputs
Compare optimization outputs from the Basic Model and the final Model Graphically depict Compare Tables

Review

Review Model Components Structure Cost Constraints Infeasibility Analysis Optimization Results

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