Thierry Moyaux

Information Sharing as a Coordination Mechanism for Reducing the Bullwhip Effect in a Supply Chain

The bullwhip effect is an amplification of the variability of the orders placed by companies in a supply chain. This variability reduces the efficiency of supply chains, since it incurs costs due to higher inventory levels and supply chain agility reduction. Eliminating the bullwhip effect is surely simple; every company just has to order following the market demand, i.e., each company should use a lot-for-lot type of ordering policy. However, many reasons, such as inventory management, lot-sizing, and market, supply, or operation uncertainties, motivate companies not to use this strategy. Therefore, the bullwhip effect cannot be totally eliminated. However, it can be reduced by information sharing, which is the form of collaboration considered in this paper. More precisely, we study how to separate demand into original demand and adjustments. We describe two principles explaining how to use the shared information to reduce the amplification of order variability induced by lead times, which we propose as a cause of the effect. Simulations confirm the value of these two principles with regard to costs and customer service levels

Supply Chain Management and Multiagent Systems: An Overview

This chapter introduces the topic of this book by presenting the fields of supply chain management, multiagent systems, and the merger of these two fields into multiagent-based supply chain management. More precisely, the problems encountered in supply chains and the techniques to address these problems are first presented. Multiagent systems are next broadly presented, before focusing on how agents can contribute to solving problems in supply chains.

Multi-Agent coordination based on tokens: reduction of the bullwhip effect in a forest supply chain

In this paper, we focus on the supply chain as a multi-agent system and we propose a new coordination technique to reduce the fluctuations of orders placed by each company to its suppliers in such a supply chain. This problem of amplification of the demand variability is called the bullwhip effect. To reduce such a bullwhip effect, we propose a technique based on tokens to achieve a decentralized coordination. Precisely, classical orders manage the demand itself whereas tokens manage effects on company inventory due to variations of this demand. Finally, the proposed approach is validated by the Wood Supply Game, which is a supply chain model used to make players aware of the bullwhip effect. We experimentally verify that our coordination technique leads to less variable orders (i.e. the standard deviation of orders is reduced) while inventory levels are not excessively high but sufficient to avoid backorders.

Multi-Agent Simulation of Collaborative Strategies in a Supply Chain

The bullwhip effect is the amplification of the order variability in a supply chain. This phenomenon causes important financial cost due to higher inventory levels and agility reduction. In this paper, we study, for each company in a supply chain, the individual incentive to collaborate to reduce this problem. To achieve this, we simulate a supply chain inspired by the Quebec forest industry, in which each company is an agent that uses one of three ordering schemes. Each ordering scheme represents a level of collaboration. One run of the simulation is done with fifty (50) weeks for each of the 36 = 729 combinations of these 3 ordering schemes among the 6 companies of the simulation. In each run, we evaluate each company¿s inventory holding and backorder costs. These outcomes are used to build a game in the normal form, which is next analyzed using Game Theory. In particular, we find two Nash equilibria incurring the minimum cost of the supply chain. We also note that there are no Nash equilibria in which some companies do not collaborate: collaborating companies have no incentive to stop collaboration.

An Agent Simulation Model for the Quebec Forest Supply Chain

A supply chain is a network of companies producing and distributing products to end-consumers. The Quebec Wood Supply Game (QWSG) is a board game designed to teach supply chain dynamics. The QWSG provides the agent model for every company in our simulation. The goal of this paper is to introduce this simulation model. For this purpose, we first outline the QWSG, and then describe with mathematical equations each company in our simulation. Finally, three examples illustrate the use of our simulation to study collaboration in supply chains. More precisely, we study incentives for collaboration at both the supply chain and company level.

A supply chain as a network of auctions

We propose and study a model of supply chains as networks of auctions. Specifically, each company in our model is represented according to the Supply Chain Councils SCOR model, and the companys trading strategy is adapted from a model proposed by Steiglitz and colleagues. Our study of this model, implemented with the JASA auction simulator, shows that price dynamics are more complicated than simply balancing consumption demands, capacities for transformation, and raw material supplies. In addition, we identify three patterns of price dynamics, explain their cause, and propose rules linking initial market conditions with the occurrence of these patterns.

Towards Service-Oriented Ontology-Based Coordination

Coordination is a central problem in distributed computing. The aim is towards flexible coordination, managed at run-time, in open, dynamic environments. This approach would benefit from an explicit common vocabulary for coordination and hence, in a previous paper, we modelled coordination in an ontology, describing the activities carried out and the interdependencies among these activities. The purpose of this paper is to show how such an ontology can be used alongside a set of rules to perform coordination by managing the interdependencies among activities. The ontology and rules can then be used to provide a general purpose coordination tool in the form of a Web service

Spreadsheet vs. multiagent-based simulations in the study of decision making in supply chains

A game called the Quebec Wood Supply Game (QWSG) is a role-playing simulation based on the Beer Game for teaching Supply Chain (SC) dynamics, and, in particular, the bullwhip effect. In this context, this paper describes and compares two simulators based on the QWSG which may be used to study decision making and its impact on SC dynamics. We first focus on the direct implementation of the QWSG in a spreadsheet program. This spreadsheet model is the base on which we next build a more complex MultiAgent Based Simulation (MABS) in which JACK™ agents represent companies. Finally, we compare the respective advantages of each simulator. We identify the features of a SC model making a spreadsheet simulation impossible, and those for which a spreadsheet simulation is better, as good as, or worse than MABS.

Design, Implementation and Test of Collaborative Strategies in the Supply Chain

In general, game theory is used to analyze interactions for- mally described by an analytical model. In this paper, we describe a methodology to replace the analytical model by a simulation one in or- der to study more realistic situations. We use this methodology to study how the more-or-less selfishness of agents affects their behaviour. We il- lustrate our methodology with the case study of a wood supply chain, in which every company is seen as an agent which may use an ordering strategy designed to reduce a phenomenon called the bullwhip effect. To this end, we assume that every agent utility can be split in two parts, a first part representing the direct utility of agents (in practice, their inventory holding cost) and a second part representing agent social con- sciousness, i.e., their impact on the rest of the multi-agent system (in practice, their backorder cost). We find that company-agents often ap- ply their collaborative strategy at whatever their same level of social consciousness. Our interpretation of this specific case study is that every company is so strongly related with one other, that all should collabo- rate in our supply chain model. Note that a previous paper outlined this methodology and detailed its application to supply chains; our focus is now on the presentation and the extension of the methodology, rather than on its application to supply chains.

Modelling a Supply Chain as a Network of Markets

The field of agent-based computational economics (ACE) studies the macroeconomic regularities emerging from the local interactions of agents. In this paper, we describe a model of supply chains inspired by ACE. To this end, we present how we have connected sets of trading agents with markets so that any supply chain structure may be simulated. The basis of our model is a representation of a supply chain as a network in which every edge represents a marketplace and every node a set of companies. The companies in every node buy in the same market, and sell in another market. We implement this using a modification of the JAVA Auction Simulator API (JASA) which simulates a single auction. As an illustration of our model, we outline three possible studies based on results from the ACE literature, and preliminary results about the first of these studies are reported. The common objective of these three studies is to find new methods to control a complex system