Sheetal Jaisingh Kamble

Modeling landfill site selection using an integrated fuzzy MCDM approach

Landfill site selection is a complex process, which requires the evaluation of multiple criteria. Decision-makers often face difficulties in taking the right decision in a multiple attribute environment. In this paper, an integrated fuzzy-analytical hierarchy process (AHP)–the technique for order preference by similarity to ideal solution (TOPSIS)-based methodology was applied to the municipal solid waste (MSW) landfill site selection problem. To demonstrate the approach taken, a real case of Mumbai city is taken. The model was developed to suit the socio-economic and regulatory set-up. The fuzzy-analytic hierarchy process was used to make pairwise comparisons of criteria to assign weights and rank them, while F-TOPSIS was employed to rank the alternatives. It was found that the fuzzy-AHP–TOPSIS-based methodology can be a powerful guiding tool for MSW management planners. With this modeling approach, the accuracy of landfill site selection procedure can be significantly enhanced as compared to the traditional methods, thereby reducing the cost and time required. The developed methodology helps in representing and analyzing the uncertainty and error in the decision making process of landfill site selection.

Decision support system framework for performance based evaluation and ranking system of carry and forward agents

Purpose – The purpose of this paper is to present a research model that explore strategic outsourcing practices for sustainable competitive advantages. In this paper, a decision support system (DSS) for sustainable performance measurement of carry and forward agents (CFAs) is proposed. Design/methodology/approach – The importance of seven criteria as a means of selecting the best CFA for warehouses under the aspect of sustainable environment is analyzed. The criteria are compared and ranked using analytic hierarchy process (AHP) with the combined assistance of literature review and expert opinions. This study makes use of unstructured interviews of Regional Distribution Manager and senior strategic leaders of the firms. Findings – This paper discusses how strategic outsourcing can help firm to achieve desired business outcomes. The selection of best CFA gives a direction to the company to move toward excellence and provides the key areas to work upon to achieve competitive advantage. The main contribution...

Identification and evaluation of landfill site selection criteria using a hybrid Fuzzy Delphi, Fuzzy AHP and DEMATEL based approach

Landfill site selection is a complex multi-criteria and time consuming process. The present study aims to identify, evaluate, and prioritize the landfill site selection criteria and finally study the relationship between them, and the degree to which they affect or are affected by one another. In the first stage, experts’ opinion was sought to select the relevant criteria and fuzzy Delphi Method (FDM) was employed to obtain the critical factors for selection of landfill sites. Next, the fuzzy Analytic Hierarchy Process (FAHP) was used to make pairwise comparisons of selected criteria by domain experts for assigning weights to the decision criteria and to calculate their importance degree. Finally, by considering the interrelationships among the criteria, Decision-making Trial and Evaluation Laboratory (DEMATEL) technique was applied to deal with the importance and causal relationships among them, and to recognize the influential criteria of landfill site selection. Obtained results show that, the criteria of sensitive area and intra-municipality are revealed to be the top two significant influences in selecting landfill sites. By identifying the relevant criteria, the structures and interrelationships, this study can offer an insight for decision makers to understand cause-effect relationships and allow to select suitable sites.

The application of Delphi and AHP method in environmentally conscious solid waste treatment and disposal technology selection

Purpose – The purpose of this paper is to describe an application of Multi-Criteria Decision Making (MCDM) technique for the selection of waste treatment and disposal technology for municipal solid waste (MSW). Design/methodology/approach – The proposed approach is based on the integration of Delphi and Analytic Hierarchy Process (AHP) techniques. A model has been proposed to evaluate the best treatment and disposal technology. Expert opinions have been incorporated in the selection of criteria. AHP has been used to determine the weights of criteria, followed by ranking of the available technologies. Findings – Delphi method was used to derive appropriate evaluation criteria to assess the potential alternative technologies. A set of identified holistic criteria was used, representing the environmental, social, and economic aspects, as compared to the sub-criteria concept generally found in existing literature. Quantitative weightings from the AHP model were calculated to identify the priorities of alterna...

A soil biotechnology system for wastewater treatment: technical, hygiene, environmental LCA and economic aspects

Soil biotechnology (SBT) is a green engineering approach for wastewater treatment and recycling. Five SBT units located in the Mumbai region were under consideration of which holistic assessment of two SBT plants was carried out considering its technical, environmental and economic aspects and was compared with published research of other three. LCA has been done to evaluate the environmental impacts of construction and operation phase of SBT. Chemical oxygen demand (COD) and biochemical oxygen demand (BOD) removal of more than 90% can be achieved using this technology. Also, the nutrient removal proficiency (nitrate, nitrite, ammoniacal nitrogen, TKN, total nitrogen and phosphates) of this technique is good. On the other hand, SBT has low annual operation and maintenance cost, comparable to land-based systems and lower than conventional or advanced technologies. From the life cycle impact assessment, the main contributors for overall impact from the plant were identified as electricity consumption, discharges of COD, P-PO43− and N-NH4+ and disposal of sludge. The construction phase was found to have significantly more impact than the operation phase of the plant. This study suggests plant I is not relatively as efficient enough regarding sanitation. SBT provides several benefits over other conventional technologies for wastewater treatment. It is based on a bio-conversion process and is practically maintenance free. It does not produce any odorous bio-sludge and consumes the least energy.

A hybrid life cycle assessment based fuzzy multi-criteria decision making approach for evaluation and selection of an appropriate municipal wastewater treatment technology

Multiple-criteria decision-making (MCDM) has become a main area of research for dealing with complex environmental decision-making problems. In this paper, a hybrid life cycle assessment (LCA) based fuzzy MCDM methodology is developed for the evaluation and selection of appropriate municipal wastewater treatment (WTT) technology based on expert opinion and questionnaires. Further, the study also aims to identify the key evaluation criteria in the process of selecting WTT from a sustainability perspective. The use of fuzzy MCDM in wastewater management has the advantage of rendering subjective and implicit decision-making more objective and analytical, with its ability to accommodate both qualitative and quantitative data. This study provides a systematic approach towards WWT technology selection, in which four-phase procedure is proposed. First, the appropriate technology evaluation and selection criteria were derived from the literature, LCA and experts’ opinion. Next, in the second stage, the fuzzy Delphi method was used to evaluate and screen the critical factors for the evaluation of technology alternatives by interviewing the experts. Twelve criteria including sustainability and those derived from LCA and life cycle costing were obtained consisting of both qualitative and quantitative criteria. In the third stage, the weights of the selection criteria as the measurable indices of the WWT technologies were determined by fuzzy pairwise comparison matrices of analytic hierarchy process. Finally, the fuzzy the technique for order of preference by similarity to ideal solution technique was used for ranking the alternatives. The six most commonly used WWT technologies, viz. sequencing batch reactors (SBR), membrane bioreactor (MBR), moving bed bio-film reactor (MBBR), soil biotechnology, facultative aerated lagoon and activated sludge process were evaluated. The present study is the first study of its kind to develop a hybrid LCA-based fuzzy MCDM methodology for the selection of best WWT alternatives. Results illustrated that advanced technologies, MBR, SBR and MBBR are the preferred options with MBR the most preferred one followed by SBR and MBBR. The developed technology assessment framework enables decision makers to understand the complete evaluation and selection process better and provide a more accurate, effective, and systematic decision support framework. The framework is superior to existing methods since it has the capability of representing vague qualitative data and presenting all possible results with different degrees of membership. The framework developed and applied in this work will help identify appropriate WWT technologies for various decision-making situations faced while managing wastewaters.

Sustainable evaluation and selection of potential third-party logistics (3PL) providers: An integrated MCDM approach

Purpose The purpose of this paper is to efficiently assist the decision makers in evaluating and selecting the most appropriate third-party logistics (3PL) provider from environmental sustainability perspective using a two-phase model based on data envelopment analysis (DEA) and analytic network process (ANP). Design/methodology/approach The study uses an integrated approach of DEA and ANP as an evaluation and selection methodology to select an efficient and requisite 3PL. The integrated model is a sound technique for 3PL evaluation and selection. DEA effectively screens the maximally efficient 3PLs, whereas ANP easily performs the cumbersome process of weighting diverse criteria and ranks various alternatives according to their performance on the basis of these criteria. This study lists the prominent evaluation and selection criteria taking into consideration the environmental sustainability. Finally, a real-life industrial application is presented to demonstrate the proposed method. Findings The current research work is devoted to the emerging research topic of environmental sustainability in logistics industry and supply chain management. The results of study indicate that eco-efficient transportation and 3PLs lead better transportation planning, better inventory and warehouse management, lower inventory cost and sustainable supply chain operations. Also, the applied approach enables the decision makers to better understand the complex relationships of the relevant criteria in the decision-making process. Research limitations/implications This study does not investigate the relationships between environmental performances and differentiation advantage from the perspective of 3PLs. Also, sensitivity analysis is not performed. Practical implications The developed integrated model enables decision analysts to better understand the complete evaluation process of 3PL evaluation and selection considering environmental sustainability perspective. Furthermore, the developed approach provides a more flexible, simple, accurate, effective, and systematic decision support tool for 3PL evaluation and selection. Originality/value The current study is first of its kind to use the integrated approach in evaluation and selection of 3PLs from environmental sustainability perspective considering the inter-dependencies among the evaluation and selection criteria.

A hybrid approach using data envelopment analysis and artificial neural network for optimising 3PL supplier selection

Today third party logistics (3PL) service providers are into almost all the businesses right from providing raw material to packaging. 3PLs are also getting involved in customers concerned with operations. At a suitable price and consideration of all affecting criteria, anything can be outsourced. Any exporter needs to find a smart balance of what to perform in-house and what to hire outside providers to do (i.e., increase verticals and reduce horizontal supply chain operations). Thus, the demand of 3PL provider has become an important issue for organisations seeking quality customer service and cost reduction. The current research presents an integrated data envelopment analysis (DEA) and artificial neural networks (ANN) methodology for the evaluation and selection of 3PL providers. DEA is employed to identify the maximally efficient 3PL and to eliminate the unsuitable ones; and, ANN to rank and make the final selection. The proposed method enables decision makers to better understand the complete evaluation and selection process of 3PL selection. Furthermore, this approach provides a more accurate, effective, and systematic decision support tool for 3PL selection. Finally, an actual industrial application is presented to demonstrate the proposed method.

To examine the relationships between supplier development practices and supplier-buyer relationship practices from the supplier’s perspective

Purpose The purpose of this paper is to examine the relationships between supplier development practices (SDPs) and supplier-buyer relationship practices from the supplier’s perspective (SBRSP), and seek to understand how specific SDPs may impact a buyer’s operational performance as well as supplier-buyer relationship practices. Design/methodology/approach The authors conducted a survey of 512 respondents from the different manufacturing firms in India and applied structural equation modelling to test a structural model that proposes the impacts of various efforts of SDPs on a buyer’s performance as well as SBRSP. Findings The study concludes that SDPs and SBRSP together improve the relationship between a buyer and supplier, and this improved relationship leads to competitive advantages (CAs) followed by profitability. Results indicate that supplier perspective of buyer-supplier relationship can be improved under the condition of SDPs and SBRSP together. SDPs are driven by productive measure and competitive pressure, whereas customer uncertainty is found to be statistically insignificant. Research limitations/implications The study was carried out in North Maharashtra Industrial Zone of India, where the auto sector and machine/components manufacturing firms have been established for a considerable period of time. Results of the study are limited to manufacturing organizations predominantly focussing on the automobile sector and machine/components manufacturing firms. Practical implications This study provides significant insights into the specific impact of various SDPs and SBRSP for both academics and practitioners. SDPs along with SBRSP practices lead to improvement in the relationship leading to CAs. SBRSP suggests that trust, long-term commitments and the supplier’s perspective are important practices for relationship improvement. Originality/value The current study attempts to identify what are the success factors for the supplier-buyer relationship from the supplier’s perspective and SDPs and how the supplier-buyer relationship can be improved under the condition of SDPs and SBRSP. Hence, the aim is to develop a more thorough understanding of the outcomes of a supplier-buyer relationship improvement from both buyer’s and supplier’s perspective, under the conditions of supplier development to achieve CAs leading to profitability. Furthermore, the study analyses the effect of the improved supplier-buyer relationship for achieving CAs leading to profitability.

Application of Hybrid Firefly Algorithm-Tabu Search Technique to Minimize the Makespan in Job Shop Scheduling problem

The Job shop scheduling problem is an important concern in the manufacturing systems. In this paper, the authors have proposed a hybrid firefly algorithm-tabu search combination technique to solve the Job shop scheduling problems. In the proposed algorithm, a complete scheme of algorithm for Job shop scheduling problems is designed and tabu search algorithm is incorporated with the aim of searching for local optimum of each individual. In order to improve the quality of solutions, in each step of the hybrid algorithms, an effective heuristic is proposed. The proposed heuristic reduces the overtime costs of operations by efficient use of the operation’s slack. The performance of the proposed algorithm is tested and evaluated solving well-known benchmarked problems. Finally, the computational results are provided for evaluating the performance and effectiveness of the proposed solution approaches. The results have proved the superiority of proposed approach to other methods such as particle swarm optimization, genetic algorithm in terms of both efficiency and success rate. KEywoRdS Firefly Algorithm, Heuristic, Job Shop Scheduling Problem, Makespan Minimization, Tabu Search Algorithm