International Journal of Advanced Operations Management (7 papers in press)
A TOPSIS, VIKOR and DEA Integrated Evaluation Method with BELIEF Structure under Uncertainty to Rank Alternatives
by Amir Amini, Alireza Alinezhad, Fahimeh Yazdipoor
Abstract: Across diverse science branches and fields multi-criteria decision making (MCDM) methods have received much attention from researchers and practitioners in evaluating, assessing and ranking alternatives as a sub-discipline and full-grown branch of operations research. This study proposes a combined method, based on a new compromised solution method and data envelopment analysis (DEA) to evaluate the efficiency of decision-making units (DMUs). By using the technique for order of preference by similarity to ideal solution (TOPSIS) and VIKOR method, in the new compromised programming approach two concepts are considered simultaneously. First, the optimal alternative is closer to positive ideal solution (PIS) and farther from negative ideal solution (NIS). Second, the proposed method provides a maximum group utility for the majority and a minimum of an individual regret for the opponent. In this method weight of efficiency witch obtained from new compromised solution method is multiplied by the weight of CCR model of DEA. The problem involves BELIEF parameters in the solution procedure. Thus, the new proposed method that applied the advantages of TOPSIS, VIKOR and DEA and belief structure simultaneously was used as a group decision making problem to exploit many experts judgments. Finally, to illustrate the proposed method, an illustrative example is provided.
Keywords: TOPSIS; VIKOR; DEA; Compromised Solution Method; Belief Structure.
Exploring the relationships between continuous improvement and predictive analytics
by Lanndon Ocampo, Brian Galli
Abstract: This study aimed to examine the elements and applications of Predictive Analytics (PA) models within the field of Continuous Improvement (CI). While the roles of data science, PA, and Big Data have been explored in the current literature (e.g., supply chain management), fragmented insights scarcely exist concerning the role of PA on CI initiatives. Articles concerning the role of PA and BI in CI projects were utilized in a systematic literature review. Furthermore, the paper stresses the vital role that Big Data Analytics plays in both CI and PA during decision-making. The paper studies other important CI and PA aspects that pertain to Continuous Improvement projects, which are aspects that are often overlooked in the existing literature. The findings from this study emphasize the critical role that PA tools and concepts can and should have in CI initiatives. Critical organizational and operational structures also need to be implemented to establish and maintain the use of PA tools and concepts in CI initiatives. Overall, this paper serves to fill the gap that overlooks the relationship between these two variables.
Keywords: Data; Predictive Analytics; Continuous Improvement; Business Intelligence; Big Data.
Time-Cost Trade-off in a Multi index Bi-criteria Fixed Charge Transportation Problem
by Sungeeta Singh, Renu Tuli, Deepali Sarode
Abstract: This paper is motivated by the necessity of finding efficient time-cost trade-off pairs for Multi Index Bi-criteria Fixed Charge Transportation Problem (MIBCFCTP) where the time criteria assumes greater significance than the cost criteria and is therefore minimized first. An algorithm is developed to find the time-cost trade-off pairs for the MIBCFCTP. So far no study on time-cost pairs of MIBCFCTP has been undertaken, a gap which the proposed algorithm aims to fulfil. Results of a numerical illustration are obtained by the proposed algorithm by extended Vogels approximation Method. Although the proposed algorithm follows a completely different approach than the existing methods of finding cost-time trade off pairs for the MIBCFCTP, however both being optimization methods their optimal solutions are comparable and it is observed that the proposed algorithm is a better alternative in MIBCFCTPs if time minimization holds priority over cost minimization.\r\n\r\n
Keywords: Multi Index transportation problem; time-cost trade-off pair; fixed charge.
OPTIMIZING THE FINANCIAL PERFORMANCE OF SUPPLY CHAIN A CASE STUDY
by Saleeshya P.G, Vinayak Rajan, Nigil Premkumar
Abstract: This paper is an outcome of a study carried out in a brake manufacturing company in India. Based on the literature review, field study and industry study, we have identified various enablers of financial supply chain. The objective of this paper is to strengthen the financial supply chain by eliminating the non-value added elements, optimizing the inventory levels and finally reducing the rejection level of poor quality products by ranking them according to their severity of defects. By identifying these factors and forces, an organization can channel its resources in the most effective way in order to enhance the achievement potential of its various performance indicators.Value Stream Mapping has been used to eliminate the non-value added processes and thereby helped the company to reduce the production lead-time.The 0-1 Knapsack methodology enabled us to optimize the value of goods flowing through the processes, with outputs showing a commendable increase in the financial chain of the process. Data Envelopment Analysis provides an insight into what the important indices must be, so that each step in the inspection process carried out is made efficient, thereby minimizing the rejection levels.
Keywords: Supply Chain Management; Financial Supply Chain; Value Stream Mapping; Inventory Analysis; Knapsack Methodology; Data Envelopment Analysis.
The Design of a Knowledge-based System for Quality Management in Healthcare: Case Study
by Yousuf Al Khamisi, Mohammed Khurshid Khan, Edurardu Munive-Hernandez
Abstract: The current healthcare systems have numerous gaps that need to be filled to reach the best practice. Healthcare organizations have used different Quality Management (QM) tools to monitor and control its services.
This paper presents a novel approach to design and validate a hybrid Knowledge-Based System (KBS) to evaluate QM of healthcare Environment (QMHE) using a hybrid system that has not been used before. The proposed system will be combined with Gauge Absence Perquisite (GAP) method to sustain a successful operation of the large number of Key Performance Indicators (KPIs) that involved in QMHE and to detect the gap between each KPI and the anticipated point. Employment of KB system offers the chance to deal with users in an appropriate way and to support in the decision-making process. Moreover, by including instructive features, the KB system can be used as a learning device for quality managers in healthcare organizations. It firstly focuses on the KB components, followed by the GAP methodology and then the application of the KB-QMHE at a tertiary hospital in Oman. Finally, a summary of the complete KB-QMHE outcomes of its application there is shown.
The system will support the healthcare governance to enhance the patient safety culture and QM efficiency. Out of 354 KB rules answered, the system has categorised 225 as GPs and the remaining 128 as BPs. The 128 bad points are categorised into different problem categories (20 PC-1, 34 PC-2, 34 PC-3, 40 PC-4, and 0 PC-5) where they represent the actions that need to be enhanced to reach the desired level of quality management.
Keywords: Knowledge based (KB) – Gauging Absence of Pre-requisite (GAP) - Quality Management in Healthcare (QMHC) - Expert System (ES).
MINIMISING THE MAKESPAN IN OPEN SHOP SCHEDULING PROBLEMS USING VARIANTS OF DISCRETE FIREFLY ALGORITHM
by Hussain Lal, Vishnu K R, A. Noorul Haq
Abstract: Minimising makespan in open shop scheduling problem is the aim of this research work. The scheduling problems consist of n jobs and m machines, in which each job has Ooperations. The processing time for 50 open shop scheduling problems was generated using a linear congruential random number generator. A non-traditional algorithm called Discrete Firefly Algorithm is proposed to minimise the makespan of open shop scheduling problems and this method is referred as A1. Discrete Firefly Algorithm is also hybridized along with other heuristic algorithms in two ways: i). Firefly Algorithm is hybridized with Longest Total Remaining Processing on other Machines and local search algorithms which is referred as A2. ii). Firefly Algorithm is hybridized with Simulated Annealing and referred as A3. Novelty of this work focuses on the application of open shop scheduling problems in quality control of a production industry.
Keywords: Makespan; Discrete Firefly Algorithm; Hybrid Meta-heuristic Algorithms.
A stochastic model of a production-inventory system with consideration of production disruption
by Rubayet Karim, Koichi Nakade
Abstract: In this paper, we develop a stochastic production-inventory model that faces random production disruption. In each fixed time planning horizon, the inventory position is affected by production disruption. The production disruption time and the disruption recovery time in a single planning horizon are stochastic. The process of the inventory levels at the beginning of the time horizon is formulated by using a finite state discrete-time Markov chain. We derive expressions of the transition probability and the long-run average cost. The optimum solution is obtained through numerical experiments. The result shows that under the circumstance of production time constraint, the incorporation of safety stock in a disruption prone production inventory system helps to minimize the long run average cost. Finally, sensitivity analysis has been given to demonstrate the usefulness of the model. This model assists decision makers to not only determine the optimal safety stock quantity but also reveal distinct effect and/or joint impacts of individual cost parameters, disruption probability on the decision regarding selection of safety stock.
Keywords: disruption recovery time; production disruption; production-inventory system; safety stock; optimization.