Supply chain management
AHMADREZA REZAEI; LIU QIONG
Abstract
Supply chain network design and resilient supplier selection play an important role in supply chain risk management to deal with various operational and disruption risks. In this paper, we develop a robust mathematical bi-objective, multi product model to consider resilient supplier and uncertainty in ...
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Supply chain network design and resilient supplier selection play an important role in supply chain risk management to deal with various operational and disruption risks. In this paper, we develop a robust mathematical bi-objective, multi product model to consider resilient supplier and uncertainty in supply chain network design across multi period and multi products simultaneously, and this study offer optimal solutions for resilient supplier selection and order allocation. First we show a mixed-integer linear programming model with two objective functions, The first objective function maximizes the total profit, while the second maximizes the total supplier resilience score, where Fuzzy SECA have been used to obtain the five resiliency criteria weights and obtain the resilience scores for the objective function. we can rank the resilient suppliers using the fuzzy SECA method . we proposed an approach for coordination between production planning, supplier selection, and order allocation. The ε-constraint method was used to obtain optimum amounts of decision variables to maximize the profit for a real case study. Finally, a Pareto solution analysis has been done for the tradeoff between robustness and resilience.the results show that how uncertainty parameters in the supply chain can affect the objective function. furthermore, this paper finds show that with supplier resilience score 4000, the first objective function of model present highest value, therefore in this point we can have resilient supplier with maximum profitability.
Engineering Optimization
Elnaz Farhang zad; Reza Ehtesham Rasi; Davood Gharakhani
Abstract
This paper examines the use of hybrid metaheuristic algorithms to optimize order quantity in a single manufacturer-multi-supplier two-level JIT supply chain in production system. Over the years, production systems have largely been controlled by either MRP (Material Requirements Planning), JIT (Just ...
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This paper examines the use of hybrid metaheuristic algorithms to optimize order quantity in a single manufacturer-multi-supplier two-level JIT supply chain in production system. Over the years, production systems have largely been controlled by either MRP (Material Requirements Planning), JIT (Just in Time) or OPT (Optimized Production Technology) paradigm. In the supply chain environment, traditional material demand planning does not consider the supplier's supply capacity and economic benefits, which is not conducive to the long-term cooperation of upstream and downstream enterprises in the supply chain. The main goal of this paper is to optimize ordering batches based on MRP and JIT in supply chain. There is limited research designing and optimizing the supply chain / procurement network. This study is among the first to integrate supplier selection to optimize performance indicators in supply chain network design considering minimization of total cost of JIT supply chain order batch coordination adjustment model. The BOM constraints and MRP formulation principles of product production are followed to minimize the supply chain the total cost of downstream companies’ inventory, transportation, out of stock, and crashing is the target. The MRP-led supply chain ordering batch collaborative optimization model is constructed; the manufacturer’s main production plan is adjusted to change the procurement plan to obtain supplier supplies according to the scheme, an improved discrete particle swarm optimization algorithm and genetic algorithm is designed to solve the model; the feasibility of the model is verified by an example. The effectiveness of the algorithm is proved through the analysis and comparison of the algorithm results.
Engineering Optimization
Faeze Momeni Rad; Mahdi Razaghi; Farzad Fathi
Abstract
Today, we can easily utilize drones to perform a wide range of tasks, whether by employing semi or fully autonomous flight modes or controlling them remotely. However, a significant drawback of current drone deployment methods is the limited operational time due to battery constraints. To address the ...
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Today, we can easily utilize drones to perform a wide range of tasks, whether by employing semi or fully autonomous flight modes or controlling them remotely. However, a significant drawback of current drone deployment methods is the limited operational time due to battery constraints. To address the battery limitations of indoor drones, a solution is proposed wherein wireless chargers are strategically placed within the coverage area of the drones' flight paths. This research paper presents an optimization algorithm that determines the ideal number of wireless charging stations needed to cover the entire area to ensure continuous charging capability throughout the entire flight duration. This work proposes an optimization framework that solves this non-deterministic polynomial-time hardness problem effectively. The algorithm is assessed by comparing its results with those of other algorithms. To evaluate the performance of our proposed approach, we conducted comparisons with several recent algorithms. Our algorithm has demonstrated superior speed compared to other algorithms.
Inventory, logistics, and transportation
Ibrahim Madugu Abdulrahman; Umar Ali Umar; Ayodeji Nathaniel Oyedeji
Abstract
Despite being the 16th-largest tomato producer in the world with the potential to dominate tomato exports, Nigeria still faces challenges, including a lack of crucial production inputs, low yields, outdated technology, significant postharvest losses (PHL), and a lack of infrastructure for processing ...
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Despite being the 16th-largest tomato producer in the world with the potential to dominate tomato exports, Nigeria still faces challenges, including a lack of crucial production inputs, low yields, outdated technology, significant postharvest losses (PHL), and a lack of infrastructure for processing and promotion. Although the PHL in tomato production and promotion are well understood worldwide, Nigeria still has a sizable knowledge gap in postharvest handling and management. So, to evaluate the perspectives of the key players (farmers, traders/middlemen, transporters/logistics, and processors) in this value chain, this study constructed a zone-specific production system, postharvest handling, and losses model for tomatoes. Three hundred fifty samples from the four districts comprised the value chain actors' survey, comprising 200 farmers, 115 traders/middlemen, 25 transporters/logistics, and 10 processors. A standardised questionnaire was used to perform the one-on-one quantitative interview. The study's findings indicated that most transporters had at least two losses, and at least one dealer had lost money. The main players in the supply chain cited problems such as the lack of market avenues, storage technologies, processing factories, close markets, and inefficient transportation methods. Furthermore, loading and unloading, breakage, rot, and accidents account for most tomato PHL losses. Therefore, it is advised that Nigeria's rich tomato market be exploited by establishing suitable processing facilities, appropriate sponsorship for farmers, and developing suitable transportation routes.
Supply chain management
Hadi rahmani fazli; hamid reza teymori
Abstract
Supply chain management constitutes a strategic discipline involving the meticulous coordination of planning, execution, and efficient control in directing the flow of raw materials, works-in-progress, finished goods, and pertinent information from origin to consumption. This intricately woven process ...
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Supply chain management constitutes a strategic discipline involving the meticulous coordination of planning, execution, and efficient control in directing the flow of raw materials, works-in-progress, finished goods, and pertinent information from origin to consumption. This intricately woven process profoundly influences all dimensions of industries and enterprises; therefore, a meticulous understanding of its opportunities and threats holds paramount significance in the landscape of industry and commerce. So, evaluating industries' resilience to existing risks is pivotal, underscoring the importance of managing supply chain risks. The global landscape has witnessed profound late-century breakthroughs, leading to the heightened complexity of supply chains. This complexity exposes supply chains to various risks, requiring managers to navigate environmental uncertainties arising from sudden shifts in demand, supply, and production processes within fiercely competitive environments. Consequently, risk management has emerged as a critical facet of effective supply chain management. This study employed structural equation modeling (SEM) and Amos software for analysis, utilizing random sampling based on Morgan's table to collect 385 observations from managers of manufacturing joint-stock companies, ranging from production workshop supervisors to higher positions, through a questionnaire. Findings indicate that preventive risk mitigation can trigger supply and manufacturing risks, subsequently leading to delivery risks, indicating a cascade effect of supply-side risks on downstream supply chains. Consequently, focusing on reducing supply risks can be advantageous in mitigating production and delivery risks. Furthermore, economic uncertainty, with coefficients of 1.1, 2.8, and 1.95, significantly influences supply, production, and delivery risks within the supply chain, resulting in reduced profitability and economic stability. Policymakers are urged to take action to minimize market uncertainties. Additionally, since competitive intensity exhibits a negative correlation with supply chain risks, measures should be taken to intensify industry competition by enforcing anti-monopoly legislation.
Other
seyed sadegh hosseini; Mohammadreza Yamaghani; Soodabeh Poorzaker Arabani
Abstract
Emotional computing synergizes the understanding and quantification of emotions, drawing on diverse data sources such as text, audio, and visual indicators. A challenge arises when attempting to discern authentic emotions from those concealed deliberately via facial cues, vocal nuances, and other communicative ...
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Emotional computing synergizes the understanding and quantification of emotions, drawing on diverse data sources such as text, audio, and visual indicators. A challenge arises when attempting to discern authentic emotions from those concealed deliberately via facial cues, vocal nuances, and other communicative behaviours. By integrating multiple physiological and behavioural signals, more profound insights into an individual's emotional state can be achieved. Historically, research has predominantly concentrated on a singular facet of emotional computing. In contrast, our study offers an in-depth exploration of its pivotal domains, encompassing emotional models, Databases (DBs), and contemporary developments. We commence by elucidating two prevalent emotional models, followed by an examination of a renowned sentiment analysis DB. Subsequently, we delve into cutting-edge methodologies for emotion detection and analysis across varied sensory channels, elaborating on their design and operational principles. In conclusion, the fundamental principles of emotional computing and its real-world implications are discussed. This review endeavours to provide researchers from academia and industry with a holistic understanding of the latest progress in this domain.
Case studies in industry and services
Robert S Keyser; Emily Rodriguez-Jacobo; Christina Scherrer
Abstract
Dental decay is the most common chronic disease in children. Fluoride varnish (FV) is a preventive oral health service with proven effectiveness at reducing dental caries in dental and primary care settings. The objective of this study was to determine how long it takes to apply FV treatments during ...
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Dental decay is the most common chronic disease in children. Fluoride varnish (FV) is a preventive oral health service with proven effectiveness at reducing dental caries in dental and primary care settings. The objective of this study was to determine how long it takes to apply FV treatments during primary care well visits to address one of the most common barriers as reported by pediatricians – lack of time. FV treatment videos were collected at six clinics in Georgia with rigorous time studies conducted on each video to determine the Standard Time for the FV treatment process as well as the FV Application Component of the process and reasons for delays. Median Standard Times varied by clinic, ranging from 67.7 seconds to 166.9 seconds with an overall median of 109.7 seconds. This results in per FV application labor costs of approximately $2.38 for pediatricians, $1.16 for registered nurses, and $0.53 for medical assistants. Findings from this study support the inclusion of FV applications as a common practice during primary care well visits.
Decision analysis and methods
sara Ait Bahom; Lotfi Chraïbi; Naoufal Sefiani
Abstract
Quality Management System QMS plays a crucial role in each company that aims to gain a competitive advantage. However, the QMS implementation requires a competent staff. Therefore, companies need a tool that will help them select the most competent candidates ...
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Quality Management System QMS plays a crucial role in each company that aims to gain a competitive advantage. However, the QMS implementation requires a competent staff. Therefore, companies need a tool that will help them select the most competent candidates for quality positions. To this aim, we have developed a new fuzzy hybrid approach based on the integration of the 2-tuple linguistic representation model with the Distance to the Ideal Alternative (DIA) method, which enables assessing candidates without distortion of the initial information. In this article, we present an illustrative example of ranking candidates for a quality coordinator position to demonstrate the validity and efficiency of our approach. In addition, we compare our approach with the most well-known and used classification approach, which is based on the use of the TOPSIS method.
Performance evaluation and benchmarking
malihe Ebrahimi
Abstract
Performance measurement is an annual process that evaluates employee performance and productivity against predetermined goals. Performance management is a determining factor in raising salaries and promoting employees. It can accurately examine the skills, strengths, and weaknesses of employees. So, ...
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Performance measurement is an annual process that evaluates employee performance and productivity against predetermined goals. Performance management is a determining factor in raising salaries and promoting employees. It can accurately examine the skills, strengths, and weaknesses of employees. So, it is very essential. In this paper, indicators are determined based on a Balanced Scorecard (BSC) to evaluate the performance of wood industry employees. For this purpose, 47 indicators are suggested and investigated by a questionnaire, of which 38 are confirmed using the nonparametric Wilcoxon’s signed-rank. The confirmed indicators are ranked using the TOPSIS and SAW methods. BCS has four dimensions, the dimension of growth and learning, the dimension of internal processes, the dimension of customer, and the dimension of finance. According to the results, the dimension of growth and learning is more important in the wood industry. Among the sub-indicators, the indicator of performing assigned tasks, the indicator of traffic and attendance, and the indicator of trust and responsibility are three critical indicators in the performance of wood industry employees.
Supply chain management
Mohammad Reza Razdan; Saeed Aghasi; Sayyed Mohammad Reza Davoodi
Abstract
Supply chain risk management involves identifying, ranking, and adopting appropriate strategies to control and deal with risks that could disrupt chain performance. These risks can be caused by different issues and descriptions and surveys about these risks are associated with uncertainty, ambiguity, ...
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Supply chain risk management involves identifying, ranking, and adopting appropriate strategies to control and deal with risks that could disrupt chain performance. These risks can be caused by different issues and descriptions and surveys about these risks are associated with uncertainty, ambiguity, qualitativeness and incomplete and sometimes contradictory information. Therefore, their ranking needs the techniques that can model the mentioned issues. neutrosophic logic makes it possible to model propositions with uncertainty, incomplete information, ambiguity, qualitativeness, and even inconsistency. Accordingly, the approach of the present study is to use a combined method of neutrosophic hierarchical analysis and TOPSIS for ranking the risk. Core of this paper is proposed a hybrid decision making method for identification and ranking of supply chain management by a Neutrosophic analytical hierarchy process and TOPSIS approach. The case study is Mobarakeh Steel Company of Isfahan and three criteria including resilience, agility and robustness are considered as major strategies to deal with risk and seventeen risk-related issues are ranked as options. The results show that government constraints, economic and environmental risks, inventory shortages, technology risk, forecast risk and financial (cash) problems are the most important risks threatening the supply chain. Therefore, we believe that the proposed framework provides managers with valuable knowledge for decision making.
Computational modelling
Seyed Hamid Emadi; Abolfazl Sadeghian; Mozhde Rabbani; hassan dehghan dehnavi
Abstract
We consider a continuous model of the optimal control of the customer dynamics based on marketing policies as a non-autonomous system of ODEs. The model tracks the history of the simultaneous changes from the beginning to the current time for the evolution of the company’s regular, referral, and ...
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We consider a continuous model of the optimal control of the customer dynamics based on marketing policies as a non-autonomous system of ODEs. The model tracks the history of the simultaneous changes from the beginning to the current time for the evolution of the company’s regular, referral, and potential customers. We then present a new supervised machine learning algorithm for the numerical simulation of the problem. The proposed learning algorithm implements a polynomial kernel to simplify the formulation of the method. To avoid computational complexity, the Bernstein kernels are used to get a simple optimization marketing strategy by using the support vector regression in least-squares framework. Some numerical experiments are carried out to support the proposed model and the method. The method provides approximate numerical results with high accuracy by kernels of polynomials of low degree. The running time of the method is also illustrated versus the increasing number of training points to see the polynomial behavior of the running time.
production planning
fahimeh tanhaie
Abstract
Mixed-model assembly is a particular set of production lines assembling a family of product models with similar specifications. Designing paced assembly lines faces two primary problems: balancing and sequencing. The balancing quality is closely associated with the described production sequence. Although ...
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Mixed-model assembly is a particular set of production lines assembling a family of product models with similar specifications. Designing paced assembly lines faces two primary problems: balancing and sequencing. The balancing quality is closely associated with the described production sequence. Although these two are problems of one assembly method, they do not occur simultaneously; balancing poses a problem during the line designing, whereas sequencing becomes problematic at the fluctuating demand of markets. The present research presents a balancing and sequencing problem and the proper times to set up the machines between tasks. Unlike a majority of published studies, this paper contains two successive tasks' setup times in dynamic periods, in which periods also impact the flowing period. A mathematical is described with a number of objective functions, reducing the inappropriate assembly line sequence, reducing setup cost, and reducing the inappropriate product balance and the impact of this situation on incomplete tasks. Thus, the literature has presented several metaheuristic algorithms to solve the problems nearly optimally. This study uses a multi-objective particle swarm optimization algorithm, a suitable approach, to create models and solutions. Various problems are designed in different sizes and compared, and the decision variable sensitivity is investigated to prepare managerial intuitions. The findings propose that the presented algorithm can solve the research problems more efficiently.
Supply chain management
habib zare ahmadabadi; ALI Saffari Darberazi; Fatemeh Zamzam; Mohammad Sadegh Babakhanifard; mehrdad kiani; Elham Mofatehzadeh
Abstract
Review of previous research shows that a systematic and comprehensive approach to the factors and dimensions of Supply Chain Resilience (SCR) has received less attention in this field. Therefore, the aim of this study is to design a model of factors influencing SCR. This research is considered applied ...
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Review of previous research shows that a systematic and comprehensive approach to the factors and dimensions of Supply Chain Resilience (SCR) has received less attention in this field. Therefore, the aim of this study is to design a model of factors influencing SCR. This research is considered applied and development-oriented in terms of its objective and was conducted in the tile and ceramic industry in Yazd province. In doing so, the study primarily investigated publications indexed on scientific databases, extracting the factors affecting SCR through a systematic approach and the meta-synthesis method. Following that, a model was constructed that consisted of 33 factors falling under five dimensions: 1) production and distribution management, 2) communication and participative management, 3) financial and information management, 4) human resources management, and 5) risk and crisis management. The findings revealed that such factors as “having a strong relationship with suppliers”, “using lean production and eliminating wastes”, “technological flexibility in production”, “implementing integrated Information Technology (IT) infrastructures in the SC”, and “safety stock of materials” were the most important factors affecting resilience in the SC. Generally speaking, what distinguish this study from the others in this field are the new and scientific framework of factors that it proposes through a systematic approach and the identification of the most important factors, which could serve as a guideline to senior managers and decision-makers.
Decision analysis and methods
Kaveh Fahimi; Ali Jafari Shahrestani; Ali Reza Zamaninejad; Fereshteh Kaboli
Abstract
This paper addresses the problem of constructing a performance assessment model. The developed model is constructed based on strategic management, intelligence systems, and expert ideas, and then it is implemented in Tehran municipality to show acceptable results for mayors. The proposed model consists ...
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This paper addresses the problem of constructing a performance assessment model. The developed model is constructed based on strategic management, intelligence systems, and expert ideas, and then it is implemented in Tehran municipality to show acceptable results for mayors. The proposed model consists of 10 steps, including team construction, vision consideration, process identification, indicator selection, weight calculation, data collection, data Extract-Transform-Load, data warehouse, analysis and reporting, feedback, and improvement processes. Analytical Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution are used for weight calculations and ranking the city's distinct. In addition, we use the Simple Weighted Mean method in four different data normalization ways and standardize the data to compare the results and use a criterion to select the robust answer. Moreover, we compare our model with the European Foundation for Quality Management model and Balance Scorecard. The proposed model is conducted at offices of plan monitoring, project control, and performance evaluation in planning, human capital development, and council affairs department at Tehran municipality.
Manufacturing and Logistics
Taha Hossein Hejazi; Mirmehdi Seyyed-Esfahani; Hurieh Dezhahang; Donya Ramezani
Abstract
The challenge of designing a closed-loop supply chain (CLSC) under conditions of uncertainty and partial disruptions is complex and demanding. The concept of a closed-loop supply chain involves integrating reverse logistics into the traditional forward supply chain to establish a sustainable and environmentally ...
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The challenge of designing a closed-loop supply chain (CLSC) under conditions of uncertainty and partial disruptions is complex and demanding. The concept of a closed-loop supply chain involves integrating reverse logistics into the traditional forward supply chain to establish a sustainable and environmentally friendly system. However, uncertainties and partial disruptions create significant obstacles to achieving an efficient and dependable CLSC. In order to address these challenges, the concept of chance constraint is introduced, allowing for the consideration of probabilistic uncertainties in decision-making. The goal is to develop a robust CLSC model capable of effectively managing uncertain parameters such as demand, rate of return, and product quality. The Markowitz method is utilized to address uncertainty in the objective function by combining the mean with a coefficient of standard deviation. The study's results demonstrate that incorporating uncertainty into the model leads to increased profitability compared to the deterministic model. The uncertain model is more responsive to demands and considers the dynamics of confidence inventory, leading to improved decision-making. Strategic decisions, such as the number of production, distribution, and destruction facilities, remain consistent in both models. However, the capacity of destruction centers in the uncertain model is slightly smaller due to the consideration of uncertain product quality. Furthermore, incorporating uncertainty into the model has contributed to enhancing the model's clarity and facilitating improved decision-making. This increase in profitability can be attributed to the model's heightened responsiveness to demands, as well as its dynamic approach to managing confidence inventory.
