Arijit Bhattacharya

Supplier selection paradigm: An integrated hierarchical QFD methodology under multiple-criteria environment

A concurrent engineering approach integrating analytic hierarchy process (AHP) with quality function deployment (QFD) in combination with cost factor measure (CFM) has been delineated to rank and subsequently select candidate-suppliers under multiple, conflicting-in-nature criteria environment within a value-chain framework. Engineering requirements and customer requirements governing the selection decision have been identified. The hierarchical QFD methodology allows the decision maker (DM) to rank the candidate-suppliers considering both CFM and the subjective factors. The sensitivity of the proposed methodology is elucidated considering a parameter called objective factor decision weight. The devised methodology has been tested with the dataset adopted from Yahya and Kingsman [89]. Liu and Hai [51] tested their model with the same dataset. A comparative analysis using design of experiment has been elucidated so as to demonstrate the efficacy of the devised hierarchical concurrent engineering approach.

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firm’s decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers’ performances meet the industry and environment standards with effective human resource.

Soft-sensing of level of satisfaction in TOC product-mix decision heuristic using robust fuzzy-LP

Product-mix decision through theory of constraints (TOC) should take into account considerations like the decision-maker’s (DM) level of satisfaction in order to make product-mix decision a robust one. Sensitivity of the decision made, needs to be focused for a bottle-neck-free, optimal product-mix solution of TOC problem. A membership function (MF) has been suitably designed in the present work, first in finding out the degree of imprecision in the product-mix decision, and thereafter to sense the level of satisfaction of the DM. Inefficiency of traditional linear programming (LP) in handling multiple-bottleneck problem through TOC has been discussed through an illustrative example. Comparison of traditional LP over fully fuzzified-LP (FLP) model has also been addressed to elucidate the advantages of FLP in TOC. Key objective of this work is to guide DMs in finding out the optimal product-mix with higher degree of satisfaction with lesser degree of fuzziness under tripartite fuzzy environment.

Distance-based consensus method for ABC analysis

A distance-based multi-criteria consensus framework on the concepts of ideal and negative-ideal solutions is presented for the ABC analysis of inventory items. This article demonstrates a way of classifying inventory items using the TOPSIS (‘Technique for Order Preference by Similarity to Ideal Solution’) model. The methodology has been applied in a pharmaceutical company located in the heart of Kolkata, India. The technique takes into account various conflicting criteria having incommensurable units of measurement. Unit cost, lead time, consumption rate, perishability of items and cost of storing of raw materials have been considered for the case study. By using TOPSIS, the items are ranked in categories A, B and C. The suitability, practicability and effectiveness of the TOPSIS method used in ABC classification have been judged using the analysis of variance (ANOVA) technique. A simulation model has been used to compare the proposed model with that of the traditional ABC classification technique.

Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF

The present research work deals with a logistic membership function (MF), within non-linear MFs, in finding out fuzziness patterns in disparate level of satisfaction for Multiple Criteria Decision-Making (MCDM) problem. This MF is a modified form of general set of S-curve MF. Flexibility of this MF in applying to real world problem has also been validated through a detailed analysis. An example illustrating an MCDM model applied in an industrial engineering problem has been considered to demonstrate the veracity of the proposed technique. The approach presented here provides feedback to the decision maker, implementer and analyst and gives a clear indication about the appropriate application and usefulness of the MCDM model. The key objective of this paper is to guide decision makers in finding out the best candidate-alternative with higher degree of satisfaction with lesser degree of vagueness under tripartite fuzzy environment.

A solution method for a two-layer sustainable supply chain distribution model

This article presents an effective solution method for a two-layer, NP-hard sustainable supply chain distribution model. A DoE-guided MOGA-II optimiser based solution method is proposed for locating a set of non-dominated solutions distributed along the Pareto frontier. The solution method allows decision-makers to prioritise the realistic solutions, while focusing on alternate transportation scenarios. The solution method has been implemented for the case of an Irish dairy processing industrys two-layer supply chain network. The DoE generates 6100 real feasible solutions after 100 generations of the MOGA-II optimiser which are then refined using statistical experimentation. As the decision-maker is presented with a choice of several distribution routes on the demand side of the two-layer network, TOPSIS is applied to rank the set of non-dominated solutions thus facilitating the selection of the best sustainable distribution route. The solution method characterises the Pareto solutions from disparate scenarios through numerical and statistical experimentations. A set of realistic routes from plants to consumers is derived and mapped which minimises total CO2 emissions and costs where it can be seen that the solution method outperforms existing solution methods.

A fully fuzzified, intelligent theory-of-constraints product-mix decision

The present research work outlines a fuzzified approach using fuzzy linear programming (FLP) using a suitably designed smooth logistic membership function (MF) for finding fuzziness patterns at disparate levels of satisfaction for theory of constraints-based (TOC) product-mix decision problems. The objective of the present work is to find fuzziness patterns of product-mix decisions with disparate levels of satisfaction of the decision-maker (DM). Another objective is to provide a robust, quantified monitor of the level of satisfaction among DMs and to calibrate these levels of satisfaction against DM expectations. Product-mix decision should take into account considerations such as the DMs level of satisfaction (sometimes called ‘emotions’) in order to make the decision a robust one. Sensitivity of the decision has been focused on a bottleneck-free, optimal product-mix solution of a TOC problem. The inefficiency of traditional linear programming (LP) in handling multiple-bottleneck problems using TOC is discussed using an illustrative example. Relationships among the degree of fuzziness, level of satisfaction and the throughput of modified TOC guide decision-makers (DM) under tripartite fuzzy environment in obtaining their product-mix choice trading-off with a pre-determined allowable fuzziness.

Integrated low-carbon distribution system for the demand side of a product distribution supply chain: a DoE-guided MOPSO optimiser-based solution approach

This article contributes to distribution system literature on three inter-linked aspects viz. formulation of a novel integrated low-carbon/green distribution system for the demand side of a Supply Chain (SC) with a single product and multiple consumers, i.e. drop-off points, a novel and robust solution approach through a Design of Experiment (DoE)-guided Multiple-Objective Particle Swarm Optimisation (MOPSO) optimiser and exhaustive analysis of the solutions (i.e. prioritisation, ranking and scenario analysis). The total costs, CO2 emission and the traversed distances of the vehicles during transportation are optimised. The optimisation model for the strategic decision-making is formulated by effectively integrating the 0–1 mixed-integer programming with a green constraint based on Analytic Hierarchy Process. Due to the computationally NP-hard characteristic of the model, a systematic and technically robust DoE-guided solution approach is designed using a commercial solver – modeFRONTIER®. DoE guides the solution through the MOPSO optimiser in order to eliminate the un-realistic set of feasible and optimal solution sets. A popular multi-attribute decision-making approach, TOPSIS, evaluates the solutions found from the Pareto optimal solution space of the solver. Finally, decision-makers’ preferences are analysed for monitoring the changes in the controlling parameters with respect to the changes in the decisions. A scenario analysis of the events by considering alternative possible outcomes is also conducted. It is found that the implemented methodology successfully routes the vehicles with optimal costs and low-carbon emission thus contributing to greening the environment on the demand side of a SC network.

Green manufacturing supply chain design and operations decision support

This special issue of International Journal of Production Research provides a platform for sharing the knowledge base, recent research outputs and a review of recent developments highlighting the critical aspects of green manufacturing supply chain design and operations decision support. The special issue includes 15 contributions presenting new and significant research in the relevant area. Contributions mainly present either a novel green/sustainable manufacturing supply chain design and operations decision support approach applied to a problem, or a state-of-the-art method on green/sustainable factors in supply chain design and operations. The article delineates an overview of the contributions and their significance, and an introspection on the ‘green’ factors involved.

Design of a resilient shock absorber for disrupted supply chain networks: a shock-dampening fortification framework for mitigating excursion events

This article interweaves the widely published empirical frameworks with a new paradigm proposing stochastic dynamic decision-making tools that could be employed for capturing the trade-offs among multiple and conflicting-in-nature criteria so as to provide a design of a resilient shock absorber (RSA) for disrupted supply chain network (SCN). Modern SCNs encounter ‘excursion events’ of different kinds mainly due to uncertain and turbulent markets, catastrophes, accidents, industrial disputes/strikes in organisations, terrorism and asymmetric information. An ‘excursion event’ is an unpredictable event that effectively shuts down or has a relatively large negative impact on the performance of at least one member of a system for a relatively long amount of time. In this article, design of an analytical framework has been conceptualised that allows an SCN to avoid propagating the ill effects of the ‘excursion events’ further and maintains the network at a desired equilibrium level. A broad analytical view of econophysics has been conceptualised using the definition of a ‘system’ from physics. An example derived from the 9/11 case has been delineated in order to illustrate the efficacy of the proposed design. The devised RSA facilitates the assessment of resiliency strategies for SCNs prone to excursion events that are characterised by low probability of occurrence and high impact. The shock-dampening fortification framework also enables practitioners to identify and assess quantitatively the islands of the excursion events in SCN.