S. G. Deshmukh

Select supplier-related issues in modelling a dynamic supply chain: potential, challenges and direction for future research

This paper is aimed at providing a broad review of the main approaches to supplier-related issues especially supplier selection, supplier–buyer relationships, supplier–buyer flexibility in relationships in a dynamic supply chain, through the description of the main characteristics, techniques, ongoing developments and research activities. Also, the issues relating to integration of core processes across organisational boundaries through improved communication, partnerships, alliances and cooperation are addressed, with its inherent focus on Web-enabled collaboration among the suppliers and the buyers. The aim of this paper is to consolidate the existing research efforts concerning the supplier-related issues, and to identify promising emerging issues for further study in this area. More specifically, this work analyses how diverse modelling techniques such as agent technology, petri nets, fuzzy logic and data mining can be applied to support dynamic supply chain configurations with reference to supplier-related issues.

A new approach for evaluating agility in supply chains using Fuzzy Association Rules Mining

Besides its effectiveness, supply chain management (SCM) is a complex process because of the stochastic and dynamic nature, multi-criterion and ever-increasing complexity of supply chains. Furthermore, companies have realized that agility is essential for their survival and competitiveness. Consequently, there is no generally accepted method by researchers and practitioners for designing, operating and evaluating agile supply chains. Moreover, the ability to build agile supply chain has developed more slowly than anticipated, because technology for managing agile supply chain is still being developed. Therefore, in this paper, we develop a new approach based on Fuzzy Association Rule Mining to support the decision makers by enhancing the flexibility in making decisions for evaluating agility with both tangibles and intangibles attributes/criteria such as Flexibility, Profitability, Quality, Innovativeness, Pro-activity, Speed of response, Cost and Robustness. Also, by checking the fuzzy classification rules, the goal of knowledge acquisition can be achieved in a framework in which evaluation of agility could be established without constraints, and consequently checked and compared in several details. Efficacy and intricacy of the proposed approach for finding fuzzy association rules from the database for evaluating agility is demonstrated with the help of a numerical example.

What's the buzz about moving from ‘lean’ to ‘agile’ integrated supply chains? A fuzzy intelligent agent-based approach

The ability to build lean and agile supply chains has not developed as rapidly as anticipated, because the development of technology to manage such concepts of lean/agile for integrated supply chains is still under way. Also, due to ill-defined and vague indicators, which exist within leanness/agility assessment, many measures are described subjectively by linguistic terms, which are characterized by vagueness and multi-possibility, and the conventional assessment approaches cannot suitably or effectively handle such dynamic situations. In this paper, we propose a novel approach to model agility (which includes leanness) and introduce dynamic agility level index (DALi) through fuzzy intelligent agents. Generally, it is difficult to emulate human decision making if the recommendations of the agents are provided as crisp, numerical values. The multiple intelligent agents used in this study communicate their recommendation as fuzzy numbers to accommodate ambiguity in the opinion and the data used for modelling agility attributes for integrated supply chains. Moreover, when agents operate based on different criteria pertaining to agility like flexibility, profitability, quality, innovativeness, pro-activity, speed of response, cost, robustness, etc., for integrated supply chains, the ranking and aggregation of these fuzzy opinions to arrive at a consensus is complex. The proposed fuzzy intelligent agents approach provides a unique and unprecedented attempt to determine consensus in these fuzzy opinions and effectively model dynamic agility. The efficacy of the proposed approach is demonstrated with the help of an illustrative example.

Supplier selection using fuzzy association rules mining approach

Owing to ill-structured, dynamic environments and the presence of multiple decision-makers with conflicting viewpoints, comprehension, analysis and support of the supplier evaluation process becomes more and more difficult. Moreover, with the complexities of issues such as the role of leadership, the influence of group formation, and analysis of disagreements, it cannot be predictable that there will ever exist a solution to cope with all imprecise, multi-criteria/multi-actor situations. A fuzzy association rules-based approach may be suited for the judgement of human subjects. In this paper, we develop an approach based on Fuzzy Association Rule Mining to support the decision makers by enhancing the flexibility in making decisions for evaluating suppliers with both tangibles and intangibles attributes. Also, by checking the fuzzy classification rules, the goal of knowledge acquisition can be achieved in a framework in which assessments could be established without constraints, and consequently checked and compared in several details. The efficacy and intricacy of the proposed model for finding fuzzy association rules from the database for supplier assessment is demonstrated with the help of numerical examples.

Revisiting information systems to support a dynamic supply chain: issues and perspectives

This article is aimed at providing a broad review of the main approaches to information related issues in a dynamic supply chain, through the description of the main characteristics, techniques, ongoing developments and research activities. The literature is examined from the perspective of the existing information systems that support supply chain dynamics at operational and strategic levels, with its inherent focus on web-enabled collaboration among supply chain partners. Various issues related to integration of core processes across organisational boundaries through improved communication, partnerships, alliances and cooperation in vague and uncertain conditions are also addressed. We review the recent trends in supply chain management and analyse how diverse modelling techniques such as agent technology and Petri net can be applied to support dynamic supply chain configuration. The purpose of this article is to consolidate the existing research efforts concerning the issues related to information systems in dynamic supply chains, and to identify promising emerging issues for further study in this area.

Modelling and analysis of supply chain dynamics: a High Intelligent Time (HIT) petri net based approach

This paper proposes a generic modelling and analysis approach to integrate and capture all process-related information for complex dynamics and distributed supply chains. Two configurations viz. the make-to-stock (MTS) and the assemble-to-order (ATO) are analysed by a novel High Intelligent Time (HIT) petri net. It serves as both an inference model for rule-based systems and a platform for knowledge verification/validation. The model enables availability of timely information across various stages of the supply chain and effectively utilises the information for improved performance. It serves as an important tool for modelling of information flows and different interactions in intermodal transport chain.

A Negotiation-to-Coordinate (N2C) Mechanism for Modeling Buyer-Supplier Relationship in Dynamic Environment

In this article, a novel Negotiation-to-Coordinate (N2C) mechanism is proposed to explore the interactive nature of the buyer-supplier relationships for dynamic environments. The proposed N2C mechanism uses prioritized fuzzy constraints to represent trade-offs among the different probable values associated with the negotiation issues and to signify how agents should make concessions. Supervisor agent in the N2C mechanism takes into account the conflicts of interest of buyer’s agent and supplier’s agent and the proposal and plan generated by supervisor agents helps in resolving the true and potential conflicts of interests for buyer’s agent and supplier’s agent. The proposed computational framework based on fuzzy constraints is suited for captur-ing the dynamics by modeling trade-offs between different attributes of a product leading to a fair and equitable deal for both suppliers and buyers. The efficacy of the proposed approach is demonstrated through an illustrative example.

e-Commerce and supply chains: Modelling of dynamics through fuzzy enhanced high level petri net

Although information plays a major role in effective functioning of supply chain networks (SCNs), studies that deal specifically with the dynamics of supply chains are few. This problem is relatively new since fast communications and the means to employ it for effective management of supply chains did not exist till recently. In order to provide a vehicle for dynamic modelling and analysis of supply chain operations in vague and uncertain environments, we propose a fuzzy enhanced high level petri net (FEHLPN) model. The proposed model captures the capability of petri nets for graphical and analytical representation of dynamic SCNs with the management of uncertain information provided by fuzzy logic. The dynamics associated with two production planning and control policies are modelled, viz. make-to-stock and assemble-to-order in vague and ambiguous situations in electronic commerce environment. A fuzzy set and fuzzy truth-values are attached to an uncertain fuzzy token to model imprecision and uncertainty. The proposed FEHLPN incorporates essential aspects of rule-based systems, such as conservation of facts, refraction, and closed-world assumption.

Enhancing flexibility in supply chains: Modelling random demands and non-stationary supply information

The faster parts, information and decisions flow through supply chains, the faster they can respond to customer needs and to the demands of the market. In the last decade, interest has been focused on the volatile market conditions and thus, the issue of demand information sharing is paid much attention. The principal objective of this study is to understand the potential values of sharing timely supply information with random demands at retail outlets. This paper proposes a theoretically rigorous framework for the modelling, qualitative analysis and computation of solutions to supply chain network problems within an equilibrium context in the case of non-stationary demands and information associated with supply chains. More specifically, a mathematical model to understand the potential values of sharing timely supply information with random demands is presented in this research. In dynamic supply chain networks, an unforeseen change may occur at any material and gradually influence the material flow at downstream stages with time. Therefore, in this paper, the impact of the change from the time aspect and the expenditure aspect is quantified respectively. By implementing the proposed algorithm, a participant at the downstream stage can figure out how long and how much the change may impact on its own performance just when the change occurs on the upstream stage. The aim of this research is not only to demonstrate the existence of bullwhip effect, but also to quantify it, i.e. to quantify the increase in variability at each stage of the supply chain and derive the market equilibrium conditions. Efficacy of the proposed approach is demonstrated with an illustrative numerical example.

A new approach to model goal and plan conflicts in a dynamic supply chain

A single supply chain configuration will neither be optimal nor efficient under dynamic and uncertain conditions, where objectives may conflict. Thus, the issue of dynamic configuration of supply chains needs serious research attention. In this paper, we combine a high level petri net with probabilistic reasoning as probabilistic petri nets to model a Multi-agent system (MAS) and detecting together goal and plan conflicts dynamically and concurrently for supply chain networks. We model supply chain dynamics based on conflicts. An integrated framework to tackle conflicts includes two stages: Conflict Recognition (CR) and Conflict Investigation (CI). CR module acts as a monitor to dynamically detect different conflicts; once conflicts identified, conflict investigation module is triggered to evaluate and rank the conflicts, which indicates to what extent the conflict will impact the agents behavior. The model explicitly captures the interactions among supply chains and within supply chains.