Fuzzy time series forecasting for supply chain disruptions

2015 ◽  
Vol 115 (3) ◽  
pp. 419-435 ◽  
Author(s):  
Felix T.S. Chan ◽  
Avinash Samvedi ◽  
S.H. Chung
Keyword(s):  
Time Series ◽  
Supply Chain ◽  
Moving Average ◽  
Discrete Event ◽  
Bullwhip Effect ◽  
Fuzzy Time Series ◽  
Supply Chain Disruptions ◽  
Content Type ◽  
Forecasting System ◽  
A Chain

Purpose – The purpose of this paper is to test the effectiveness of fuzzy time series (FTS) forecasting system in a supply chain experiencing disruptions and also to examine the changes in performance as the authors move across different tiers. Design/methodology/approach – A discrete event simulation based on the popular beer game model is used for these tests. A popular ordering management system is used to emulate the behavior of the system when the game is played with human players. Findings – FTS is tested against some other well-known forecasting systems and it proves to be the best of the lot. It is also shown that it is better to go for higher order FTS for higher tiers, to match auto regressive integrated moving average. Research limitations/implications – This study fills an important research gap by proving that FTS forecasting system is the best for a supply chain during disruption scenarios. This is important because the forecasting performance deteriorates significantly and the effect is more pronounced in the upstream tiers because of bullwhip effect. Practical implications – Having a system which works best in all scenarios and also across the tiers in a chain simplifies things for the practitioners. The costs related to acquiring and training comes down significantly. Originality/value – This study contributes by suggesting a forecasting system which works best for all the tiers and also for every scenario tested and simultaneously significantly improves on the previous studies available in this area.

scholarly journals ANALISIS MODEL MANAJEMEN PERMINTAAN SCM NETWORK DAN PERAMALAN PERMINTAAN PADA PENJUALAN BUSANA MUSLIM MENGGUNAKAN METODE LINEAR REGRESSION

2021 ◽  
Vol 5 (1) ◽  
pp. 28-32
Author(s):  
Vela Maghfiroh ◽  
◽  
Yusuf Amrozi ◽  
Qushoyyi Bondan Prakoso ◽  
Mochamad Adam Aliansyah
Keyword(s):  
Time Series ◽  
Supply Chain ◽  
Data Analysis ◽  
Linear Regression ◽  
Error Rate ◽  
Moving Average ◽  
Bullwhip Effect ◽  
Lifestyle Changes ◽  
Linear Regression Method ◽  
Analysis Techniques

Supply chain management is very important for a company because it will affect supply performance in the company. Doing business in this era has many challenges that must be faced, especially in the Muslim clothing business. The way to stabilize the demand diagram of the Muslim clothing business, retailers are required to manage the supply chain so that they can meet the total demand. The object of this research is Rabbani Cirebon which was obtained from a literature study published in a journal entitled "Trend of Muslim Lifestyle Changes" from Banjarmasin State Polytechnic. The journal has sales data based on product types from monthly in 2016. From this data will be processed and analyzed using data analysis techniques. This data analysis technique uses time series forecasting data analysis techniques. From this time series method, this research uses moving average and linear regression. After modeling the data, the forecast error is measured using MAD, MAPE, RMSE, and MSE. The overall MSE results were 103731.8 and RMSE 322.0743. The benefit of demand forecasting is to reduce the Bullwhip Effect, plan future resources, for example, such as stock management, place control, product distribution, and demand for raw materials so as to make the right decisions. The results showed that the linear regression method has better forecasting than the moving average because linear regression has a smaller error rate than the moving average. But even so, the error rate of this study is still very large, so it is necessary to do more research to minimize the error rate.

Sustainable resource management in a supply chain: a methodological proposal combining zero-inflated fuzzy time series and clustering techniques

2020 ◽  
Vol 33 (5) ◽  
pp. 1059-1076 ◽  
Author(s):  
Henrique Ewbank ◽  
José Arnaldo Frutuoso Roveda ◽  
Sandra Regina Monteiro Masalskiene Roveda ◽  
Admilson ĺrio Ribeiro ◽  
Adriano Bressane ◽  
...  
Keyword(s):  
Time Series ◽  
Supply Chain ◽  
Fuzzy Time Series ◽  
Sustainable Supply Chain ◽  
Demand Forecast ◽  
Content Type ◽  
Clustering Techniques ◽  
Sustainable Supply Chains ◽  
Sustainable Resource Management ◽  
Excess Of Zeros

PurposeThe purpose of this paper is to analyze demand forecast strategies to support a more sustainable management in a pallet supply chain, and thus avoid environmental impacts, such as reducing the consumption of forest resources.Design/methodology/approachSince the producer presents several uncertainties regarding its demand logs, a methodology that embed zero-inflated intelligence is proposed combining fuzzy time series with clustering techniques, in order to deal with an excessive count of zeros.FindingsA comparison with other models from literature is performed. As a result, the strategy that considered at the same time the excess of zeros and low demands provided the best performance, and thus it can be considered a promising approach, particularly for sustainable supply chains where resources consumption is significant and exist a huge variation in demand over time.Originality/valueThe findings of the study contribute to the knowledge of the managers and policymakers in achieving sustainable supply chain management. The results provide the important concepts regarding the sustainability of supply chain using fuzzy time series and clustering techniques.

Managing the great bullwhip effects caused by COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saad Zighan
Keyword(s):  
Supply Chain ◽  
Situation Awareness ◽  
Bullwhip Effect ◽  
The Body ◽  
Just In Time ◽  
Exploratory Research ◽  
Content Type ◽  
Body Of Knowledge ◽  
Geographical Distances ◽  
Purchasing Behaviour

Purpose This study aims to answer the question of how firms can deal with the great bullwhip effects caused by COVID-19? Design/methodology/approach An exploratory research method has been adopted and evidence was collected based on 41 online interviews. Findings The study finds that the bullwhip effect is caused by the sudden changes in customers purchasing behaviour during the pandemic and the businesses’ inaccurate anticipation of the situation. Managing the bullwhip effects caused by COVID-19 requires situation awareness, localisation and an intelligent supply chain. Situation awareness is a vital concept in emergency response, knowing what is going to figure out what should be done. Furthermore, reducing the geographical distances between the firm and other parties in the supply chain, which equates to supply chain localisation, enforces just-in-time inventory. Finally, supply chain digitalisation is no longer an option; implementing such a solution enables end-to-end visibility, collaboration, flexibility and optimisation of orchestration of the supply chain. Research limitations/implications This study presents indicators explaining how organisations can deal with the great bullwhip effects caused by COVID-19. Originality/value The ongoing outbreak of the COVID-19 pandemic has brought about significant challenges for supply chain management, and this study contributes to the body of knowledge and proposes a model of reducing the bullwhip effects.

Air quality management using genetic algorithm based heuristic fuzzy time series model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lalit Bhagat ◽  
Gunjan Goyal ◽  
Dinesh C.S. Bisht ◽  
Mangey Ram ◽  
Yigit Kazancoglu
Keyword(s):  
Genetic Algorithm ◽  
Air Pollution ◽  
Time Series ◽  
Air Quality ◽  
Quality Management ◽  
Fuzzy Time Series ◽  
Selection Algorithm ◽  
Content Type ◽  
Proposed Model ◽  
Adaptive Time

PurposeThe purpose of this paper is to provide a better method for quality management to maintain an essential level of quality in different fields like product quality, service quality, air quality, etc.Design/methodology/approachIn this paper, a hybrid adaptive time-variant fuzzy time series (FTS) model with genetic algorithm (GA) has been applied to predict the air pollution index. Fuzzification of data is optimized by GAs. Heuristic value selection algorithm is used for selecting the window size. Two algorithms are proposed for forecasting. First algorithm is used in training phase to compute forecasted values according to the heuristic value selection algorithm. Thus, obtained sequence of heuristics is used for second algorithm in which forecasted values are selected with the help of defined rules.FindingsThe proposed model is able to predict AQI more accurately when an appropriate heuristic value is chosen for the FTS model. It is tested and evaluated on real time air pollution data of two popular tourism cities of India. In the experimental results, it is observed that the proposed model performs better than the existing models.Practical implicationsThe management and prediction of air quality have become essential in our day-to-day life because air quality affects not only the health of human beings but also the health of monuments. This research predicts the air quality index (AQI) of a place.Originality/valueThe proposed method is an improved version of the adaptive time-variant FTS model. Further, a nature-inspired algorithm has been integrated for the selection and optimization of fuzzy intervals.

Linking supply chain professional's competencies to resilience in a turbulent world

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Idrees Asghar ◽  
Haris Aslam ◽  
Amer Saeed
Keyword(s):  
Supply Chain ◽  
Knowledge Sharing ◽  
Structural Equation ◽  
Corporate Training ◽  
Research Model ◽  
Supply Chain Disruptions ◽  
Content Type ◽  
Knowledge Based ◽  
Equation Modelling ◽  
Antecedents And Consequences

PurposeThis research aims to understand how competencies for supply chain professionals are developed and how they can affect the manager's performance, especially the manager's resilience in times of significant supply chain disruptions.Design/methodology/approachA research model was developed based on a comprehensive literature survey in the area of individual competencies grounded in the knowledge-based view of the firm. We tested our research model using a quantitative, survey-based study with a sample of 175 Pakistani supply chain managers. The hypotheses were tested using structural equation modelling (SEM).FindingsThe analysis identified corporate training and knowledge sharing as the main antecedents of supply chain professional's competencies. It also showed that these competencies result in higher performance in the form manager's resilience and job performance.Research limitations/implicationsThis study provides a valuable framework for organisations to focus on skill-developing training and promoting a knowledge-sharing culture among employees to achieve desired performance levels.Originality/valueThis study is unique as no prior research studied such a comprehensive model of antecedents and consequences of supply chain professionals' competencies.

Bullwhip Effect Analysis in a Supply Chain

2012 ◽  
pp. 646-665
Author(s):  
Mehdi Najafi ◽  
Reza Zanjirani Farahani
Keyword(s):  
Supply Chain ◽  
Statistical Method ◽  
Moving Average ◽  
Bullwhip Effect ◽  
Effect Analysis ◽  
Forecasting Methods ◽  
Effect Measure ◽  
Forecasting Method ◽  
Efficiency And Effectiveness ◽  
Main Factors

In today’s world, all enterprises in a supply chain are attempting to increase both their and the supply chain’s efficiency and effectiveness. Therefore, identification and consideration of factors that prevent enterprises to attain their expected/desired levels of effectiveness are very important. Since bullwhip effect is one of these main factors, being aware of its reasons help enterprises decrease the severity of bullwhip effect by opting proper decisions. Now that forecasting method is one of the most important factors in increasing or decreasing the bullwhip effect, this chapter considers and compares the effects of various forecasting methods on the bullwhip effect. In fact, in this chapter, the effects of various forecasting methods, such as Moving Average, Exponential Smoothing, and Regression, in terms of their associated bullwhip effect, in a four echelon supply chain- including retailer, wholesaler, manufacturer, and supplier- are considered. Then, the bullwhip effect measure is utilized to compare the ineffectiveness of various forecasting methods. Owing to this, the authors generate two sets of demands in the two cases where the demand is constant (no trend) and has an increasing trend, respectively. Then, the chapter ranks the forecasting methods in these two cases and utilizes a statistical method to ascertain the significance of differences among the effects of various methods.

Supply chain structures for distributing surplus food

2020 ◽  
Vol 31 (4) ◽  
pp. 865-883
Author(s):  
Caroline Sundgren
Keyword(s):  
Supply Chain ◽  
Service Provider ◽  
Closed Loop ◽  
Food Distribution ◽  
Weak Links ◽  
Content Type ◽  
Different Types ◽  
Multiple Case ◽  
A Chain

PurposeNew actors have emerged in the food supply chain in response to the increased awareness of food waste and the need to distribute surplus food. The purpose of this study is to analyse the different supply chain structures that have emerged to make surplus food available to consumers.Design/methodology/approachThis study adopts a qualitative multiple-case study of three new surplus food actors: a surplus food platform, an online retailer and a surplus food terminal. Data sources included interviews, documentary evidence and participatory observations.FindingsThree different types of actor constellations in surplus food distribution have been identified: a triad, a tetrad and a chain. Both centralised (for ambient products) and decentralised supply chain structures (for chilled products) have emerged. The analysis identified weak links amongst new actors and surplus food suppliers. The new actors have adopted the roles of connector, service provider and logistics service provider and the sub-roles of mediator, auditor and consultant.Originality/valueThis paper contributes to research on closed-loop or circular supply chains for the reuse of products in the context of surplus food distribution.

Towards greater supply chain stability

2019 ◽  
Vol 35 (6) ◽  
pp. 33-35
Keyword(s):  
Supply Chain ◽  
Design Methodology ◽  
Bullwhip Effect ◽  
Global Supply Chain ◽  
Global Supply Chains ◽  
Content Type ◽  
Pertinent Information ◽  
The Stability ◽  
Practical Implications ◽  
Chain Increase

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Building a regional rather than a global supply chain can help firms guard against the damaging impact of the bullwhip effect and increase the stability of their supply chain. The possibility of better communication, greater flexibility, and ability to respond more quickly are factors that can appease the bullwhip severity. The benefits of a regional supply chain increase further in times of economic certainty, when the risk to global supply chains intensifies. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Investigating the impact of inventory inaccuracy on the bullwhip effect in RFID-enabled supply chains using colored petri nets

2019 ◽  
Vol 14 (2) ◽  
pp. 360-384 ◽  
Author(s):  
Maria Drakaki ◽  
Panagiotis Tzionas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Petri Nets ◽  
Information Sharing ◽  
Bullwhip Effect ◽  
Colored Petri Nets ◽  
Content Type ◽  
Multi Stage ◽  
The Impact ◽  
Serial Supply Chains

PurposeInformation distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.Design/methodology/approachA simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.FindingsThe bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.Research limitations/implicationsInformation sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.Originality/valueColored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.

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