Analytic hierarchy process : An overview of applications

* Starting from Need* Evolution of the Toyota Production System* Further Development* Genealogy of the Toyota Production System* The True Intention of the Ford System* Surviving the Low-Growth Period

Toyota production system : beyond large-scale production

Multi-Criteria Decision Aid (MCDA) or Multi-Criteria Decision Making (MCDM) methods have received much attention from researchers and practitioners in evaluating, assessing and ranking alternatives across diverse industries. Among numerous MCDA/MCDM methods developed to solve real-world decision problems, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily across different application areas. In this paper, we conduct a state-of-the-art literature survey to taxonomize the research on TOPSIS applications and methodologies. The classification scheme for this review contains 266 scholarly papers from 103 journals since the year 2000, separated into nine application areas: (1) Supply Chain Management and Logistics, (2) Design, Engineering and Manufacturing Systems, (3) Business and Marketing Management, (4) Health, Safety and Environment Management, (5) Human Resources Management, (6) Energy Management, (7) Chemical Engineering, (8) Water Resources Management and (9) Other topics. Scholarly papers in the TOPSIS discipline are further interpreted based on (1) publication year, (2) publication journal, (3) authors' nationality and (4) other methods combined or compared with TOPSIS. We end our review paper with recommendations for future research in TOPSIS decision-making that is both forward-looking and practically oriented. This paper provides useful insights into the TOPSIS method and suggests a framework for future attempts in this area for academic researchers and practitioners.

Review: A state-of the-art survey of TOPSIS applications

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/118683/Integrated analytic_38.pdf

Integrated analytic hierarchy process and its applications:a literature review

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Over the last decade, many healthcare organizations have adopted lean thinking to reduce wastages and to improve flow efficiency in the patient flow processes. But there is limited research done on understanding the sequence to be followed by healthcare organizations to implement lean in their different departments, and on the applicability of various lean tools in different healthcare settings. This article aims to bridge this gap, map the current state of lean in healthcare and identify future research directions. Key concepts of lean thinking are introduced, and the current body of knowledge between 2002 and 2014 is explored to answer key research questions on the application of lean in different healthcare settings. Further, this article is one of the first attempts to classify healthcare services according to the service process matrix. Results show that different healthcare services pose unique challenges to lean implementation due to their inherent characteristics of service delivery. Research oppo...

A Decade of Lean in Healthcare: Current State and Future Directions:

Simultaneous influence of market power structure, advertising and quality efforts on the optimal pricing decisions and performance of a multi-echelon supply chain under uncertainty have received sc...

Pricing decisions for three-echelon supply chain with advertising and quality effort-dependent fuzzy demand

Risk management holds a crucial role in ensuring efficiency, predictability, and coherency in supply chain operations of an enterprise. Risks are associated with every member of a supply chain network. Thus, an end-to-end risk management approach is essential to fortify the entire supply chain network. In this paper, we consider a supply chain network consisting of suppliers, manufacturers, distributors and retailers, as the representative stakeholders. In particular, we take supply chain operational, and opportunism risks into account, and investigate the roles of flexibility, and social relationship, respectively, as a mitigation approach. We develop a multi-period network equilibrium model by considering the stakeholders’ objectives of maximising profit and minimising risk. Further, the finite-dimensional variational inequality formulations are derived for the underlying network optimisation problem. An algorithm, with nice features for computations, is then applied to three simulated examples in order...

A supply chain network equilibrium model for operational and opportunism risk mitigation

static scheduling algorithms are widely used to evaluate the performance of distributed computing system. In such systems, purpose of scheduling algorithm is to allocate tasks to available processor so as to efficiently utilize this processor and to reduce the makespan, total computational cost and various other such factors, with the motive of achieving optimal solution. Scheduling algorithms are classified into two broad categories i.e., static scheduling algorithms and dynamic scheduling algorithms. In this paper we are discussing various static scheduling algorithm and numerous problems in various levels of the homogeneous and heterogeneous distributed systems. Also we are comparing these algorithms on the basis of various factors such as speedup, time complexity, scheduling length ratio, normalized scheduling length and so on.

/pdf/a-survey-of-static-scheduling-algorithm-for-distributed-359zdv9md9.pdf

Sushil Kumar

Papers

Analytic hierarchy process : An overview of applications

A Decade of Lean in Healthcare: Current State and Future Directions:

Pricing decisions for three-echelon supply chain with advertising and quality effort-dependent fuzzy demand

A supply chain network equilibrium model for operational and opportunism risk mitigation

A Survey of Static Scheduling Algorithm for Distributed Computing System