Optimization Of Supply Chain Management Research Articles

Optimizing Supply Chain Management with Retail Analysis Technique

The success of any business organization depends on efficient supply chain management (SCM) that ensures the timely delivery of products to customers. The retail analysis technique (RAT) has emerged as a powerful tool for optimizing SCM by enabling companies to identify and analyze sales trends, inventory levels, and customer demand patterns. This paper explores the use of retail analysis techniques in SCM and how they can be leveraged to enhance the efficiency and effectiveness of supply chain operations. We then present a unified RAT framework that integrates data mining, predictive analytics, and machine learning for optimizing SCM. Additionally, the paper presents a case study of a company that has successfully implemented retail analysis techniques in its SCM practices. The case study highlights the specific strategies and tactics that the company used to optimize its supply chain operations and achieve significant improvements in efficiency and performance. Our analysis shows that RAT is an effective technique for optimizing SCM, and companies that implement it can gain a competitive advantage in the marketplace.

Implementation of game theory for the selection of optimal supply chain management strategies for startups in the electronics sector

Nowadays, the level of competition in the electronics sector is very high. According to market experts, competition in the electronics sector relies not only on the development of new products, but...

Role of Information Technology in Optimization of Supply Chain Management

Role of Information Technology in Optimization of Supply Chain Management

The Importance of Transportation Management in Optimizing Supply Chain Management at Industrial Estate

Transportation management is able to integrate various components that are highly needed in order to ensure the distribution of goods and services takes place effectively and efficiently. The effects of integrated transportation systems have major contribution to business processes and the sustainability of supply chain system in an area. This study measures role of transportation management, supply chain management, and business performance which carries out business in industrial estate. Survey was conducted on employees working in manufacturing industry in Bekasi region. Analysis technique in this study uses structural equation modeling (SEM). Conclusion obtained from results of analysis states that transportation management has significant influence on supply chain management, and has significant impact on business performance, especially for manufacturing industry. In order to grow and develop and even produce optimal business performance, transportation management support with good, integrated and supported management from various sectors is needed to create superior supply chain management so that transportation management support is needed with good governance, integrated, and supported from various sectors so as to create superior supply chain management so as to ensure the availability of industry needs. Suggestions are recommended in relation to planning of transportation management systems that support needs in industrial estate so as to understand strategies that must be carried out for success of business.

A model for evaluating green credit rating and its impact on sustainability performance

The development of economic activities and social progress index leads to the governmental considerations for the environmental challenge’s issues. The Green Credit Policy (GCP) in China for manufacturing, as a part of a sustainable finance package, initiatives restrictions with suppliers to reduce harmful pollution for the environment. The study mainly validates the impact of GCP on manufacturing for diminishing the emerged pollution to the environment. The study develops Neutrosophic Multiple-Criteria Decision-Making Framework (N-MCDMF) according to neutrosophic theory and various MCDM methods of grey relational analysis (GRA), analytic network process (ANP), the Decision-Making Trial and Evaluation Laboratory technique (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to support the decision-makers with highly systematic procedures in the uncertain and inconsistent environmental conditions. The N-MCDMF evaluates the conditions of GCP and recommends the optimal Supply Chain Management (SCM) in manufacturing alternatives. A case study is presented for the validation of the issues of applicability and flexibility for the proposed N-MCDMF. The results obtained from the implementation of the N-MCDMF indicates the applicability and flexibility of the proposed approach. In addition, results show that SCM in manufacturing can provide more cooperation for the environment to reduce harmful pollution and to attain sustainability for achieving motivations under the restrictions of GCP.

Family planning science and practice lessons from the 2018 International Conference on Family Planning.

Since 2009, the International Conference on Family Planning (ICFP) has served as an opportunity for the global reproductive health community to share FP advances and practice lessons in the areas of research, programming, and advocacy. The key takeaways from all 15 tracks were grouped into six thematic areas: 1) Investing in family planning for a lifetime of returns. FP may yield different health and monetary benefits but continues to face a shortage of funding, although locally owned models provide alternative financing solutions. 2) Addressing inequities in family planning for adolescents, youth, and key populations. Marginalized populations and youth still face challenges in accessing FP. Youth-inclusive and user-centered programming show promise in addressing such challenges. 3) Reproductive justice: Abortion care, family planning, and women's wellbeing. Unsafe abortions tend to be more common among younger, poor, uneducated and rural women. Promising evidence show that providers may effectively shift from unsafe practices of dilation and curettage to safer manual vacuum aspiration or misoprostol. 4) Couple dynamics and family planning decision-making. Couples who share everyday life decision-making are more likely to use contraceptives; couple discordance on childbearing and fertility decisions directly influence women's decisions to covertly use FP. 5) Male involvement in FP programming. Male champions and advocates can successfully promote couple uptake of FP. Gender-transformative programming promotes gender equity and can directly impact behavior change. 6) Breakthroughs in novel contraceptives and systems improvement in family planning. User-centered contraceptive technologies and information systems present an opportunity to facilitate self-care and optimal supply chain management. ICFP 2018 highlighted research advances, implementation science wins, and critical knowledge gaps in global FP access and use. More research is needed to determine the scalability of novel technologies, more effective programming and service delivery models to ensure multisectoral knowledge translation and utilization by policymakers.

Logistics Optimization in Supply Chain Management using Clustering Algorithms

Today’s business environment, survival and making profit in market are the prime requirement for any enterprise due to competitive environment. Innovation and staying updated are commonly identified two key parameters for achieving success and profit in business. Considerably supply chain management is also accountable for profit. As a measure to maximize the profit, supply chain process is to be streamlined and optimized. Appropriate grouping of various suppliers for the benefit of shipment cost reduction is proposed. Data relating to appropriate attributes of supplier logistics are collected. A methodology is proposed to optimize the supplier logistics using clustering algorithm. In the proposed methodology data preprocessing, clustering and validation process have been carried out. The Z-score normalization is used to normalize the data, which converts the data to uniform scales for improving the clustering performance. By employing Hierarchical and K-means clustering algorithms the supplier logistics are grouped and performance of each method is evaluated and presented. The supplier logistics data from different country is experimented. Outcome of this work can help the buyers to select the cost effective supplier for their business requirements.

Digital Technologies in Supply Chain Management in Production

The article discusses the prospect of using digital technologies in supply chain management, as well as the main trends and features of the development of supply chain management at the plant. The article deals with issues related to the integration of blockchain technologies in the field of logistics and supply chain management. The article suggests using blockchain information technologies to optimize supply chain management processes in the context of enterprise virtualization and digital economy development. The study revealed the advantages of this approach over traditional business management technologies and logistics systems. The prospects for using blockchain technology in logistics and supply chain management are also analyzed.

Closed-loop real-time supply chain management for perishable products

Supply chain networks are dynamical systems with particular control challenges that stem from inventory deterioration and external disturbances (i.e., unanticipated consumer demand, time delays, etc.). For industries handling highly perishable inventory (e.g, fresh produce, vaccines, biologics) controlling product quality throughout the multiple echelons of the supply chain is critical to minimize inventory waste and satisfy consumer quality requirements. However, quality, as a function of time and environmental conditions (i.e., temperature, humidity, light, etc.), is difficult to model accurately resulting in unpredicted inventory spoilage. In this paper we demonstrate a novel closed-loop, feedback-based control framework that employs real-time product quality measurements for optimal supply chain management. A moving horizon approach is used to periodically update decisions (i.e., production, transportation, storage, and respective environmental conditions) based on fed-back information. We demonstrate that the postulated feedback controller effectively stabilizes the supply chain dynamics, while minimizing costs. An illustrative case study is provided.

Proposing a new model for location - routing problem of perishable raw material suppliers with using meta-heuristic algorithms

In the last three decades, an integrated approach to optimize logistics system is considered as one of the most important aspects of optimizing supply chain management. This approach involves the ties between locations of facility, allocation of suppliers/customers, structure of transportation routes and inventory control. The aim of this paper is to investigate the ordering planning of a supply chain with multi supplier, multi distribution center, multi customer and one perishable raw material. This paper provides a mathematical model taking in consideration the limitation of raw material corruptibility (perishable material) which belongs to the category of NP-hard problems. To solve the proposed model, the Ant Colony Optimization algorithm (ACO) and Particle Swarm Optimization algorithm (PSO) are employed. In order to improve performances of ACO and PSO parameters, a Taguchi experimental design method was applied to set their proper values. Besides, to evaluate the performance of the proposed model, an example of the dairy industry is analyzed by using MATLAB R 2015a. To validate the proposed meta-heuristic algorithms, the results of them were compared with together. The results of the comparison show that ACO is greater than PSO in speed convergence rate and the number of solutions iterations.

Optimization Algorithm in Supply Chain Management

Optimization in the field of Operations Research has applications in various industries, be it medicine, business, analytics or education. Likewise Supply Chain Management (SCM) is required in every industry and with the need comes various challenges to get the optimized and best quality solution. There are stochastic, analytical models working on attaining optimization in various sub events involved in SCM. Supply Chain is a network at global level used for delivering of products and services from unprocessed materials to consumers through well-structured and planned flow of information, physical distribution and money. The process of managing this supply chain is Supply Chain Management. A major work on the previous research done using various mathematical models, be it mixed integer linear, nonlinear programming or evolutionary have been depicted in this paper. The aim is to get the best result and comparative approach is focused. This article provides a detailed study on various techniques, algorithms and mathematical models in optimization of SCM and in particular it focuses on Genetic Algorithm (GA) in SCM.

Optimizing supply chain management of processed fish products in the industrial era 4.0

The UMKM which is the target of this research is the UMKM which is engaged in processing fish caught in Pasuruan Regency. There are several superior products of processed fish caught in Pasuruan Regency which are managed by UMKM so far so many and can be one alternative to improve the welfare of MSME entrepreneurs. However, from the processed fishery products to become a valuable product, a good management is needed so that the supply or availability of catched fish is sufficient in order to equalize and fulfill the desired demand. In supporting this inventory control activity, a management concept is needed that can regulate the flow of goods and information that is precise and accurate from the supply chain, namely the concept of Supply Chain Management (SCM). The focus of the research is on how to manage the supply chain of fish raw materials from captured products through research methods using Supply chain Management (SCM) with the Fuzzy Analytical Hierarchy Process (AHP) method, to then proceed with the implementation of a sales development strategy for MSME Coastal Superior Products. From the results of the analysis and discussion obtained in the determination of supplier selection criteria, a pairwise comparison between criteria, sub-criteria and alternatives using the Fuzzy AHP method to produce weights. Based on the criteria and sub-criteria in supplier selection, overall supplier A (UMKM in the Lekok District Region) was rated as the best supplier weighing 1,699, the second priority was supplier B (UMKM in the Nguling District Region) with a weight of 1,345, while supplier C (UMKM in the Region Kraton District) is the last priority with a weight of 1,098

Transportation scheduling optimization by a collaborative strategy in supply chain management with TPL using chemical reaction optimization

Optimization of supply chain management is a way of ensuring the usability of resources and related technologies at the best possible way. Transportation scheduling of vehicle and transportation nodes in supply chain management is an important factor in order to create a stable chained network by ensuring the highest amount of product distribution and lowest logistics cost. In recent years, a number of programming models like linear programming, heuristics and meta-heuristics optimization approaches are proposed by the researchers to solve this combinatorial NP-hard problem. In this paper, we have studied and analyzed the nature of transportation vehicle scheduling problem in a supply chain network with the help of third-party logistics enterprise by using a meta-heuristic algorithm called chemical reaction optimization (CRO). At first, we have classified all the transportation nodes into three distinct classifications. Then, a collaborative transportation scheduling strategy is used which is based on two significant kinds of transportation nodes. For the first two kinds of nodes, we have randomly created a large number of combined transportation routes, and the vehicle scheduling for the last standalone nodes is created by a random matrix generation. Then, we have proposed a CRO algorithm using four reaction operators with an additional repair operator to find out the best transportation routes within shortest computing time. We named our proposed algorithm as chemical reaction optimization for supply chain management (CRO-SCM). The proposed CRO-SCM algorithm is analyzed with the standard dataset from the proposed model using modified ACO-NSO algorithm which is the state of the art. In addition, a random dataset of different scales of transportation nodes is considered to evaluate the efficiency of the algorithm. Moreover, six different scales of problem sets consisting different number of nodes are adopted to analyze the performance of the proposed CRO algorithm. The simulation results demonstrate that the proposed approach is practical and efficient than existing ACO-based solutions and the experimental results are more efficient and optimal.

Study on Coffee Marketing and Farmer Organization in Pasuruan District

Complexity of coffee supply chain system encourages business actors to optimize supply chain management as an effort to increase market transparencyamong them. Consolidating in farmer organization was required to strengthen bargaining position of farmer for facing the complexity of supply chain system.The aim of this research was to analyze supply chain and marketing margin on coffee marketing; and to analyze the characteristics of coffee farmer organization.This research was conducted in Pasuruan district as one of coffee producing area in East Java. Number of respondents were 18 that consisted of 16 farmersand 2 extension officers. The respondent was determined by snowball sampling method. The data was considered a primary data and secondary data was usedas supporting data. Data were analyzed by using descriptive method and marketing margin analysis. The result showed that coffee marketing chain in Pasuruan district would lead to a relatively long and complex which was dominated by collectors. The highest profit of Arabica coffee marketing received by collectors was gained by selling green beans. On the Robusta coffee marketing, the highest profit was derived by selling fresh cherries. Farmer organizations could not be able to improve their bargaining position and market access as a result of weakness on the role and function of them.

Stochastic simulation and optimization in supply chain management

Stochastic simulation and optimization in supply chain management

Firefly Algorithm for Supply Chain Optimization

The firefly algorithm is one of the best latest bio-inspired algorithms, which proved its performance in solving continuous and discrete optimization problems. This paper presents a more detailed comparison study using a set of test functions. The main goal is the application of Firefly algorithm (FA) to solve Lot size optimization in supply chain management which is the most complex part of stock management process. A complexity that comes from the conflict between the minimization of the costs and the maximization of the level of service. For these reason, the traditional methods of lot size control have to deal with the explosion of new needs related to supply chain evolution. The optimal solutions obtained by FA are far better than the best solutions obtained by deterministic methods analyzed in the literature.

Towards an Information Technology Based Supply Chain Management System for Ghanaian Oil Marketing Companies

This study set out to propose an optimal supply chain management system for Ghanaian Oil Marketing companies. The research approach combined an inductive and deductive approach as a basis for designing the proposed system. This was based on data collected from the Oil Marketing Companies, review of literature, documents and the mode of companies› operation An optimal information technology based solution is then proposed to automate their processes for how people, activities, information, and resources are involved in moving oil products and services from supplier to consumer. A number of modular systems have been proposed, these include a Purchase Order System, GPS Fleet Tracking System, Credit Reference System and Fore Court Operations management system. It is expected that a comprehensive integration of these modules would significantly make the operations of Ghanaian oil marketing companies systems more efficient and effective.

Reducing stock-outs of essential tuberculosis medicines: a system dynamics modelling approach to supply chain management.

The under-performance of supply chains presents a significant hindrance to disease control in developing countries. Stock-outs of essential medicines lead to treatment interruption which can force changes in patient drug regimens, drive drug resistance and increase mortality. This study is one of few to quantitatively evaluate the effectiveness of supply chain policies in reducing shortages and costs. This study develops a systems dynamics simulation model of the downstream supply chain for amikacin, a second-line tuberculosis drug using 10 years of South African data. We evaluate current supply chain performance in terms of reliability, responsiveness and agility, following the widely-used Supply Chain Operation Reference framework. We simulate 141 scenarios that represent different combinations of supplier characteristics, inventory management strategies and demand forecasting methods to identify the Pareto optimal set of management policies that jointly minimize the number of shortages and total cost. Despite long supplier lead times and unpredictable demand, the amikacin supply chain is 98% reliable and agile enough to accommodate a 20% increase in demand without a shortage. However, this is accomplished by overstocking amikacin by 167%, which incurs high holding costs. The responsiveness of suppliers is low: only 57% of orders are delivered to the central provincial drug depot within one month. We identify three Pareto optimal safety stock management policies. Short supplier lead time can produce Pareto optimal outcomes even in the absence of other optimal policies. This study produces concrete, actionable guidelines to cost-effectively reduce stock-outs by implementing optimal supply chain policies. Preferentially selecting drug suppliers with short lead times accommodates unexpected changes in demand. Optimal supply chain management should be an essential component of national policy to reduce the mortality rate.

CLAUSEWITZ E A COMPLEXIDADE NO SÉCULO XXI: VISITANDO OPÇÕES PARA A LOGÍSTICA DE DEFESA NO BRASIL

This is a brief analysis with the objective of examining the Defense Logistics, in the light of the Clausewitzian Trinity, by visiting its dynamics in the international sphere and its design at the national level and, thus, highlighting the possible options to be applied in the Brazilian Defense Logistics within the framework of the 21stCentury. The study was conducted under the epistemological prism of Complexity and accommodated from a qualitative perspective. An inductive approach was chosen, supported by a method of historical and monographic procedure, combining descriptive and analytical efforts. The documentary and bibliographical research techniques were applied, collecting perspectives, later, used to substantiate the case study technique, in the examination of the complexity of the Defense Logistics in 21st Century. As a result, the influence of Clausewitz's thinking and of the complexity of the contemporary conflict scenario on Defense Logistics, both internationally and domestically, was verified. Finally, the study enabled the discussion of three latent options on Defense Logistics: the promotion of a fiscal incentive and partnership policy between the Government and the Defense Industry; the design of a strategy to reduce the bureaucracy of the procurement of defense products; and the optimization of Supply Chain Management.

Clausewitz e a complexidade no século XXI: Visitando opções para a logística de defesa no Brasil

This is a brief analysis with the objective of examining the Defense Logistics, in the light of the Clausewitzian Trinity, by visiting its dynamics in the international sphere and its design at the national level and, thus, highlighting the possible options to be applied in the Brazilian Defense Logistics within the framework of the 21stCentury. The study was conducted under the epistemological prism of Complexity and accommodated from a qualitative perspective. An inductive approach was chosen, supported by a method of historical and monographic procedure, combining descriptive and analytical efforts. The documentary and bibliographical research techniques were applied, collecting perspectives, later, used to substantiate the case study technique, in the examination of the complexity of the Defense Logistics in 21st Century. As a result, the influence of Clausewitz's thinking and of the complexity of the contemporary conflict scenario on Defense Logistics, both internationally and domestically, was verified. Finally, the study enabled the discussion of three latent options on Defense Logistics: the promotion of a fiscal incentive and partnership policy between the Government and the Defense Industry; the design of a strategy to reduce the bureaucracy of the procurement of defense products; and the optimization of Supply Chain Management.