Neuro-dynamic programming for cooperative inventory control

Abstract

Abstract-In Multi-Retailer Inventory Control the possibility of sharing set up costs motivates communication and coordination among the retailers. We solve the problem of finding suboptimal distributed reordering policies which minimize set up, ordering, storage and shortage costs, incurred by the retailers over a finite horizon. Neuro-Dynamic Programming (NDP) reduces the computational complexity of the solution algorithm from exponential to polynomial on the number of retailers.

Coordination arrival control for multi-agent systems

“…Suppose that the topology graph G.X ; E/ of the multi-agent system X D ¹x i ji D 1; 2; ; nº is undirected and connected and x i obeys the dynamic model (1). In this section, we will introduce the coordination arrival protocol of the multi-agent system X when moving to the target group R D ¹r i ji D 1; 2;…”

“…; nº is undirected and connected and that x i obeys the dynamic model (1). Assume that the multi-agent system X moves to the target group R D ¹r i ji D 1; 2;…”

A tracking control scheme for leader based multi-agent consensus for discrete-time case

“…This is partially due to the rapid development in communication and computation, and wide applications of multi-agent systems in many areas including cooperative control of mobile robots [3] , unmanned air vehicles [4] , autonomous formation flight [5] , control of multi-vehicle formations [6,7] , or non-formation cooperative control problems such as task assignment, payload transport, air traffic control, coordinated buyers [8] , cooperative inventory control [9] , coverage control for mobile sensing networks [10] , timing and congestion control in communication networks [11] . On the other hand, ubiquitous cooperative behavior in nature and human societies, such as birds flocking, fish schooling, bee dancing, ant path planning, fireflies flashing in unison, and even people clapping in phase during rhythmic [12] etc., has stimulated researchers to explore the underlying mechanisms of such collective behavior.…”

Mechanism Design for Optimal Consensus Problems

“…Coordination of agents/vehicles is an important task in several applications including autonomous formation flight [3], [4], cooperative search of unmanned air-vehicles (UAVs) [5], swarms of autonomous vehicles or robots [6], [7], [8], multi-retailer inventory control [9], [10], [11] and congestion/flow control in communication networks [12]. Distributed consensus protocols are distributed control policies based on local information that allow the coordination of multi-agent systems.…”