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

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

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

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

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

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

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

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

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