Insights on Multi-Agent Systems Applications for Supply Chain Management

In this paper, we review relevant literature on the development of multi-agent systems applications for supply chain management. We give a general picture of the state of the art, showing the main applications developed using this novel methodology for analyzing diverse problems in industry. We also analyze generic frameworks for supply chain modelling, showing their main characteristics. We discuss the main topics addressed with this technique and the degree of development of the contributions.Universidad de Sevilla V PPIT-USPiano della Ricerca Dipartimentale 2016-2018 of DICAR-UniC

On bullwhip-limiting strategies in divergent supply chain networks

The amplification of demand variation in a supply chain network (SCN) is a well-known phenomenon called the bullwhip effect. This effect generates a large volume of inefficiencies as it moves a greater number of units than necessary, increases stock and generates stock-outs. There are two different approaches for avoiding and/or limiting this detrimental phenomenon that have received attention in the literature: Collaboration and information sharing in SCNs on one hand, and the adoption of smoothing replenishment rules on the other. The effectiveness of both approaches have been often analyzed only for “serial linked” SCNs, which is a supply network structure rarely found in real-life. In order to give an insight of how these techniques would perform in more generic SCNs, a divergent SCN has been benchmarked against the classical serial SCN. The computational experience carried out show that the bullwhip effect can be considerably reduced by collaboration or the smoothing replenishment rules in divergent SCNs, but it always performs worse than the serial SCN due to its inherent complexity

Influence of Supply Chain Network Topology on the Evolution of Firm Strategies

This study investigates the influence of the topological structure of a supply chain network (SCN) on the evolution of cooperative and defective strategies adopted by the individual firms. First, a range of topologies representative of SCNs was generated using a fitness-based network growth model, which enabled cross comparisons by parameterising the network topologies with the power law exponent of their respective degree distributions. Then, the inter-firm links in each SCN were considered as repeated strategic interactions and were modelled by the Prisoner’s Dilemma game to represent the self-interested nature of the individual firms. This model is considered an agent-based model, where the agents are bound to their local neighbourhood by the network topology. A novel strategy update rule was then introduced to mimic the behaviour of firms. In particular, the heterogeneously distributed nature of the firm rationality was considered when they update their strategies at the end of each game round. Additionally, the payoff comparison against the neighbours was modelled to be strategy specific as opposed to accumulated payoff comparison analysis adopted in past work. It was found that the SCN topology, the level of rationality of firms and the relative strategy payoff differences are all essential elements in the evolution of cooperation. In summary, a tipping point was found in terms of the power law exponent of the SCN degree distribution, for achieving the highest number of co- operators. When the connection distribution of an SCN is highly unbalanced (such as in hub and spoke topologies) or well balanced (such as in random topologies), more difficult it is to achieve higher levels of co-operation among the firms. It was concluded that the scale-free topologies provide the best balance of hubs firms and lesser connected firms. Therefore, scale-free topologies are capable of achieving the highest proportion of co- operators in the firm population compared to other network topologies

A network science approach to analysing manufacturing sector supply chain networks: Insights on topology

Due to the increasingly complex nature of the modern supply chain networks (SCNs), a recent research trend has focussed on modelling SCNs as complex adaptive systems. Despite the substantial number of studies devoted to such hypothetical modelling efforts, studies analysing the topological properties of real world SCNs have been relatively rare, mainly due to the scarcity of data. This paper aims to analyse the topological properties of twenty-six SCNs from the manufacturing sector. Moreover, this study aims to establish a general set of topological characteristics that can be observed in real world SCNs from the manufacturing sector, so that future theoretical work modelling the growth of SCNs in this sector can mimic these observations. It is found that the manufacturing sector SCNs tend to be scale free with degree exponents below two, tending towards hub and spoke configuration, as opposed to most other scale-free networks which have degree exponents above two. This observation becomes significant, since the importance of the degree exponent threshold of two in shaping the growth process of networks is well understood in network science. Other observed topological characteristics of the SCNs include disassortative mixing (in terms of node degree as well as node characteristics) and high modularity. In some networks, we find that node centrality is strongly correlated with the value added by each node to the supply chain. Since the growth mechanism that is most widely used to model the evolution of SCNs, the Barabasi - Albert model, does not generate scale-free topologies with degree exponent below two, it is concluded that a novel mechanism to model the growth of SCNs is required to be developed

The impact of the supply chain structure on bullwhip effect

The aim of this paper is to study how the structural factors of supply chain networks, (i.e. the number of echelons, the number of nodes and the distribution of links) impact on its dynamics performance (i.e. bullwhip effect). To do so, we systematically model multiple structures according to a robust design of experiments and simulate such structures under two different market demand scenarios. The former emulates a stationary condition of the market, while the latter reproduce the extreme volatility and impetuous alteration of the market produced by the current economic recession. Results contribute to the scientific debate on supply chain dynamics by showing how the advocated number of echelons is not the only structural factor that exacerbates the bullwhip effect. In particular, under a sudden shock in market demand, the number of nodes and the divergence of the supply chain network affect the supply chain performance.Ministerio de Economía y Competitividad DPI2013-44461-P/DP

The impact of supply chain structures on performance.

La Tesis analiza el impacto que tiene la estructura de las redes de suministro sobre su rendimiento, concretamente sobre el “efecto látigo” o efecto bullwhip. Para ello se desarrolla una arquitectura basada en la metodología de los sistemas multi-agente, que permite el modelado de sistemas complejos. Dicha arquitectura es implementada en un software dando lugar a un simulador de redes de suministro llamado SCOPE, que permite el modelado y simulación de una amplia variedad de configuraciones de redes de suministro. SCOPE es utilizado para investigar una de las suposiciones más comunes en el campo del modelado de redes de suministro: el uso de estructuras muy sencillas en forma serial generalmente con muy pocas fases funcionales y pocos nodos. Para determinar el impacto de la estructura de la red sobre el efecto bullwhip se utiliza una estructura más compleja y más acorde con las estructuras de redes de suministro reales: la red divergente. Se realizan tres experimentos: (i) análisis comparativo del efecto bullwhip entre la red divergente y la serial; (ii) análisis comparativo de la eficacia de dos técnicas muy conocidas para la limitación del efecto bullwhip entre la red divergente y la serial; (iii) determinación de los parámetros estructurales de la red de suministro divergente y análisis estadístico para determinar si dichos parámetros estructurales impactan sobre el efecto bullwhip. Los resultados obtenidos revelan que todos los parámetros estructurales analizados impactan significativamente sobre efecto bullwhip. Además, en caso de un impulso inesperado en la demanda, el impacto de la red de suministro en el efecto bullwhip es mayor. Las técnicas para limitación del efecto bullwhip son también efectivas en redes de suministro divergentes, consiguiendo además un aumento de su robustez ante cambios bruscos inesperados en la demanda

Leveraging supply network relationships to drive performance

Effective supply chain management requires focal firms to develop capabilities to manage a myriad of multi-tier, interconnected relationships often spanning multiple industries. Conventional assessments of supply chain relationships as linear or dyadic structures, rather than as a network, limit academician and managerial approaches to overcome challenges to effectively manage supply chains. Further, empirical research on innovation and performance implications of supply network structure and its corresponding relationship dynamics is still fairly nascent. My research focuses on leveraging supply network relationships to drive performance. Specifically, in my dissertation I examine how the structural, knowledge, and dependency differences in a firm’s supply network can affect knowledge and information flow, and ultimately the firm’s innovative, operational, and financial performance. My first study (CH. 2) contributes to current research at the interface of supply chain management and innovation. My second (CH. 3) and third paper (CH. 4) incorporate the intensity of each supply network link, reflective of focal firms as customers (suppliers) that may rely heavier on a supplier (customer) based on their percentage of cost (revenue) that goes to (is generated from) that supplier (customer). All three papers extend current research findings by bringing a more holistic assessment of firms that are embedded in a supply network, addressing the need for deeper structural analysis.Ph.D