1. Dynamic Management of Food Redistribution for 412 Food Rescue
Zachary B. Rubinstein
Intelligent Coordination and Logistics Laboratory
Robotics Institute
Carnegie Mellon University

2. Dynamic Management of Food Redistribution - Brief Overview of Project
Goal: Increase 412 Food Rescue capacity to service the hungry through optimizing technology that provides
better matching of food opportunities to demand
efficient transportation options for relocating food to distribution points
Partners: 412 Food Rescue 2

3. Dynamic Management of Food Redistribution – Expected Outcomes
Higher volume of effective food redistribution
More service to high need areas
Better operational management resulting from automated assignments of food destinations and transportation options.
Advanced market-based approach to multiple-objective resource-allocation problem
Application of AI techniques for social good.
High Need Areas 3

4. Two Basic Optimization Problems
Destination problem – Given a food opportunity, determine where to deliver food to maximize benefit.
Key question: What to maximize?
Key question: Is there electronic support for this problem?
Transportation problem – Given a request to transport food, determine the person to make the delivery that maximizes utility of the transportation network.
Key question (again): What to maximize?
Key question: Can a request require multiple trips?
Should these problems be considered independently?
i.e., Is destination influenced by the ability to transport? 4

5. Auctions Using Contract Net Protocol
General Approach:
Auctions Using Contract Net Protocol
The Contract Net Protocol (CNP) is a generic protocol for distributed task allocation first specified by R. Smith (1980).
Basic Steps in CNP:
Agent receives a new task to be contracted out
Managing agent initiates an auction by announcing the task’s existence to other agents
Available agents evaluate task announcement based on eligibility and other criterion
Suitable agents submit bids for task
Managing agent awards task to most appropriate agent(s), after enough time has elapsed, based on submitted bids 5

6. Transportation Example
Bids are sent back to Manager
Bid
Time-Window: [ti, tj]
Location Dist: […]
Availability Dist: […]
Capacity
Generates Bid
Generates Bid
Generates Bid
Generates Bid
Generates Bid
Announcement
Type
Amount
Pickup Location
Delivery Location
Time Window
Generates Bid
Manager sends announcement to nodes
Assignments are sent back to nodes
Receives job request
Bids are synthesized into assignments
Generates Bid

7. Destination Problem Objectives
Distribute food equitably among non-profits.
Keep non-profits motivated to participate
Distribute food to areas with greatest need.
Distribute food based on efficiency of non-profit.
What other objectives? 7

8. Transportation Problem Objectives
Distribute food requests equitably among transporters.
Keep transporters motivated to participate
Limit visibility of lost auctions?
Restrict announcements and use iterative auctions?
Make bidding invisible?
Use same transporter for recurrent (weekly) trips
Efficiently use workforce
Minimize number of transporters to preserve network capacity?
What other objectives? 8

9. Software Architecture
Provide optimization as a web service.
Use Post statements with JSON contents
Return options
Human in the loop?
Provide communications to conduction auctions
Inside planner or outside?
Common or private database?
Search Engine
State Manager T1
Planner
Requests
Bids
Announcements
Options
Commitments 9