Prioritizing high-risk sub-groups in a multi-manufacturer vaccine distribution program

2017 ◽  
Vol 28 (2) ◽  
pp. 311-331 ◽  
Author(s):  
Sharon Hovav ◽  
Avi Herbon
Keyword(s):  
Supply Chain ◽  
High Risk ◽  
Large Scale ◽  
Decision Support Tool ◽  
Added Value ◽  
Mixed Integer ◽  
Efficient Manner ◽  
Content Type ◽  
Support Tool ◽  
Medical Burden

Purpose Annual influenza epidemics cause great losses in both human and financial terms. The purpose of this paper is to propose a model for optimizing a large-scale influenza vaccination program (VP). The goal is to minimize the total cost of the vaccination supply chain while guaranteeing a sufficiently high level of population protection. From a practical point of view, the analysis returns the number of shipments and the quantity of vaccines in each periodic shipment that should be delivered from the manufacturers to the distribution center (DC), from the DC to the clinics, and from the clinics to each sub-group of customers during the vaccination season. Design/methodology/approach A mixed-integer programming optimization model is developed to describe the problem for a supply chain consisting of vaccine manufacturers, the healthcare organization (HCO) (comprising the DC and clinics), and the population being vaccinated (customers). The model suggests a VP that implemented by a nation-wide HCO. Findings The benefits of the proposed approach are shown to be particularly salient in cases of limited resources, as the model distributes demand backlogs in an efficient manner, prioritizing high-risk sub-groups of the population over lower-risk sub-groups. In particular, the authors show a reduction in direct medical burden of consumers, such as the need for doctors, hospitalization resources, and reduction of indirect, non-medical burden, such as loss of workdays. Practical implications Drawing from the extended enterprise paradigm, and, in particular, taking consumer benefits into account, the authors suggest an operational-strategic model that creates impressive added value in a highly constrained supply chain. The model constitutes a powerful decision tool for the deployment of large-scale seasonal products, and its implementation can yield multiple benefits for various consumer segments. Originality/value The model proposed herein constitutes a decision support tool comprising operational-tactical and tactical-strategic perspectives, which logistics managers can utilize to create an enterprise-oriented plan that takes into account medical and non-medical costs.

scholarly journals An innovative decision support tool for liquefied natural gas supply chain planning

2020 ◽  
Vol 5 (1) ◽  
pp. 121-136
Author(s):  
Christos Papaleonidas ◽  
Dimitrios V. Lyridis ◽  
Alexios Papakostas ◽  
Dimitris Antonis Konstantinidis
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Natural Gas ◽  
Decision Support Tool ◽  
Liquefied Natural Gas ◽  
Maritime Transportation ◽  
Management Tool ◽  
Content Type ◽  
Support Tool ◽  
Tramp Shipping

Purpose The purpose of this paper is to improve the tactical planning of the stakeholders of the midstream liquefied natural gas (LNG) supply chain, using an optimisation approach. The results can contribute to enhance the proactivity on significant investment decisions. Design/methodology/approach A decision support tool (DST) is proposed to minimise the operational cost of a fleet of vessels. Mixed integer linear programming (MILP) used to perform contract assignment combined with a genetic algorithm solution are the foundations of the DST. The aforementioned methods present a formulation of the maritime transportation problem from the scope of tramp shipping companies. Findings The validation of the DST through a realistic case study illustrates its potential in generating quantitative data about the cost of the midstream LNG supply chain and the annual operations schedule for a fleet of LNG vessels. Research limitations/implications The LNG transportation scenarios included assumptions, which were required for resource reasons, such as omission of stochasticity. Notwithstanding the assumptions made, it is to the authors’ belief that the paper meets its objectives as described above. Practical implications Potential practitioners may exploit the results to make informed decisions on the operation of LNG vessels, charter rate quotes and/or redeployment of existing fleet. Originality/value The research has a novel approach as it combines the creation of practical management tool, with a comprehensive mathematical modelling, for the midstream LNG supply chain. Quantifying future fleet costs is an alternative approach, which may improve the planning procedure of a tramp shipping company.

The effect of investment in green technology in a two echelon supply chain under strict carbon-cap policy

2020 ◽  
Vol 27 (6) ◽  
pp. 1875-1891 ◽  
Author(s):  
Arindam Ghosh ◽  
S P Sarmah ◽  
Radhey Krishna Kanauzia
Keyword(s):  
Supply Chain ◽  
Greenhouse Gas Emission ◽  
Academic Community ◽  
Green Technology ◽  
Added Value ◽  
Mixed Integer ◽  
Chain Model ◽  
Content Type ◽  
Green Investment ◽  
The Cost

PurposeStrict carbon-cap policy is one of the basic policies proposed by the regulatory bodies to reduce the anthropogenic greenhouse gas emission. The purpose of this paper is to examine whether it is beneficial for a company to invest in green technology or not under the strict carbon-cap policy and for that a two echelon supply chain model is developed. This paper gives insight about judicious decision about investment on green technology.Design/methodology/approachMathematical modeling approach has been adopted to understand the effect of investment on green technology. All the cost and emissions parameters have been derived and the total cost (TC) and total emission equations have been formulated mathematically. Two constrained mixed-integer nonlinear programming (MINLP) problems have been formulated and solved considering with or without green investment. Further, supply chain cost is optimized without carbon constraint to understand the effect of carbon constraint.FindingsThe investment in green technology can reduce the total supply chain cost. The study reveals that handling different parameters optimally can reduce both cost and emissions.Originality/valueThis paper tries to assess the effectiveness of green investment on technology under strict carbon-cap policy on a supply chain and, thereby, added value to the existing work. It examines the role played by various parameters under strict carbon-cap policy to draw insights, which will be beneficial for the academic community and managers.

Supply Chain Modeling for a Process Industry

2017 ◽  
Vol 8 (2) ◽  
pp. 36-55 ◽  
Author(s):  
Nils-Hassan Quttineh ◽  
Helene Lidestam ◽  
Mårten Ahlstedt ◽  
Sven Olsson
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Decision Support ◽  
Programming Model ◽  
Decision Support Tool ◽  
Process Industry ◽  
Mixed Integer ◽  
Budget Process ◽  
Process Industries ◽  
Support Tool

Process industries of today differ from other industries in many aspects. The purpose of this paper is to consider these special properties of process industries when developing a mathematical model that can be used as a decision support tool for the supply chain planning for a chemical process industry in Sweden. A mixed-integer linear programming model is developed, and solutions to the model present how the products will be transported between the different sites of the company, the levels of the inventories, the setups and purchases from the external suppliers and also the production rates. The mathematical model takes many special properties regarding process industries into account. By using the results from the model and test different scenarios, the model can be used as an important support tool when making decisions. The decision support tool can for example be used in the company's budget process and thereby improve the chances of future profits increases.

scholarly journals Transportation Risk Control of Waste Disposal in the Healthcare System with Two-Echelon Waste Collection Network

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haolin Li ◽  
Yi Hu ◽  
Junyan Lyu ◽  
Hao Quan ◽  
Xiang Xu ◽  
...  
Keyword(s):  
Healthcare System ◽  
Large Scale ◽  
Programming Model ◽  
Time Windows ◽  
Decision Support Tool ◽  
Mixed Integer ◽  
Waste Collection ◽  
Routing Problem ◽  
Support Tool ◽  
Transportation Risk

This paper investigates a vehicle routing problem arising in the waste collection of the healthcare system with the concern of transportation risk. Three types of facilities abstracted from the health system are investigated in this paper, namely, facilities with collection points, facilities without collection points, and small facilities. Two-echelon collection mode is applied in which the waste generated by small facilities is first collected by collection points, and then transferred to the recycling centre. To solve this problem, we propose a mixed-integer linear programming model considering time windows and vehicle capacity, and we use particle swarm optimisation (PSO) algorithm for solving large-scale problems. Numerical experiments show the capability of the proposed algorithm. Sensitivity analysis is conducted to investigate the influence of facilities with collection points and the collection routes. This research can provide a decision support tool for the routing of waste collection in the healthcare system.

Enablers and barriers to circular supply chain management: a decision-support tool in soft wheat bread production

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marco Formentini ◽  
Luca Secondi ◽  
Luca Ruini ◽  
Matteo Guidi ◽  
Ludovica Principato
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Supply Chain Management ◽  
Circular Economy ◽  
Decision Support Tool ◽  
Soft Wheat ◽  
Wheat Bread ◽  
Chain Management ◽  
Content Type ◽  
Support Tool

PurposeThere is a limited understanding of effective strategies for tackling food loss and waste (FLW) following a circular supply chain management approach. The aim of this study is to analyze the role of the FLW Reporting and Accounting Standard for identifying FLW occurrences throughout the agri-food supply chain and facilitate their measurement. Our objective is to describe how this FLW is then reused within a circular economy (CE) perspective, thus enabling companies to implement a circular supply chain approach for effective decision-making based on the concept of waste hierarchies, the 3R and 4R rules.Design/methodology/approachAn in-depth analysis of Barilla's soft bread supply chain is provided in this study. By gathering both qualitative and quantitative data, this study investigates the implementation of the FLW standard by (1) identifying the main enablers and obstacles in measuring FLW throughout the entire production system; (2) providing a useful standardized tool for sustainable FLW measurement, minimization and reuse in other agricultural supply chains to enable circular economy approaches and (3) developing a decision-support strategy to use within the company for effective measurement, analysis and reuse according to a CE perspective.FindingsThe analyses carried out throughout Barilla's soft wheat bread supply chain provide an interesting example of a circular management system since almost nothing is lost or wasted while the value of resources is recovered through reuse thanks to a systematic and integrated measurement, representing a basis for effectively minimizing waste. The importance of developing an interconnected supply chain management emerged in order to obtain a comprehensive accounting framework for accurately quantifying and reporting the overall amount of wastage generated in the various phases of food production, paying particular attention to ex ante prevention initiatives and ex-post assessment actions.Originality/valueAn interdisciplinary approach integrating circular economy and supply chain management research streams was adopted in order to develop a decision-support tool that also includes the identification of the main facilitators and obstacles to the implementation of a comprehensive standardized accounting process that would enable companies to reduce-reuse-recycle losses and waste throughout the entire production process. Besides the studies available in the literature, the original of this study is that it focuses on organizational implications related to FLW measurement.

Designing of an agility control system: a case of an Indian manufacturing organization

2020 ◽  
Vol 15 (4) ◽  
pp. 1591-1612
Author(s):  
Bharat Singh Patel ◽  
Cherian Samuel ◽  
Goutam Sutar
Keyword(s):  
Supply Chain ◽  
Control System ◽  
Decision Support ◽  
High Performance ◽  
Decision Support Tool ◽  
Integrated Approach ◽  
Decision Variable ◽  
Content Type ◽  
Support Tool ◽  
Decision Variables

Purpose Agility is the ability of an organization to adjust its supply chain tactics and operations to respond quickly against altering business environments such as fluctuating demand pattern, supply chain disruption and global competition. An agile organization must possess a promising capability of swiftly responding to dynamic conditions while being cost-effective without compromising the efficiency. Such high-performance adaptability necessitates the role of supply chain managers to maximize the agility of the supply chain through the efficient use of input resources. Therefore, the purpose of this study to reveal a new decision support tool that would allow the key decision-makers to maximize the agility of the supply chain while deploying the input resources more effectively. Design/methodology/approach In present study, an integrated approach of popular analytic hierarchy process (AHP) and goal programming (GP) has been adopted as a potential solution methodology. AHP has been implemented to allocate the local and global weights to decision variables, whereas GP incorporates the AHP weights into the desired model. Findings It was found that the proposed decision support tool restricts the value of the decision variables for maximizing the agility and optimizing the usage of input resources. The results obtained from the model validate the objective of achieving targeted agility level within the available resource limitations. Research limitations/implications The decision support tool developed in the proposed study offers a systematic and effectively simple approach to supply chain managers with a goal of identifying the degree of focus under each decision variable in the respective manufacturing organizations. Originality/value A novel decision support tool has been developed known as an agility control system), which helps the decision-maker to achieve the required agility in the supply chain by controlling the decision variables.

Collaborative firms managing perishable products in a complex supply network: an empirical analysis of performance

2015 ◽  
Vol 20 (2) ◽  
pp. 128-138 ◽  
Author(s):  
Juan Carlos Pérez Mesa ◽  
Emilio Galdeano-Gómez
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Fruits And Vegetables ◽  
Perishable Products ◽  
Supply Network ◽  
Content Type ◽  
Sales Channels ◽  
Positive Effects ◽  
Starting Point ◽  
Supplier Relationship

Purpose – This purpose of this study is to provide empirical evidence of how cooperation is related to suppliers’ performance, a relationship that is thought to be affected by the type of customer and the extent to which the market is diversified. It analyzes horticultural exporting firms in southeastern Spain, which are the main suppliers of European markets. Together with their primary customers (large-scale retail companies such as Carrefour, Tesco and Aldi), these firms constitute a complex supply network composed of a variety of agents and sales channels. This network will be studied from the perspective of the supplier–supplier relationship that is critical to their survival. Design/methodology/approach – Starting with a detailed description of Europe’s vegetable supply chain, a hierarchical regression is used with an index of cooperation intensity, moderated by retail sales and market concentration. The authors test the hypotheses using panel data on a set of 118 horticultural marketing firms in southeast Spain for the period 2009-2011. Findings – Cooperation strategies are shown to have positive effects on performance (market creation, promotion, quality, training, joint supply purchases and research ventures). Moreover, the retail channel and market diversification are observed to have a positive effect on the relationship between cooperation and the supplier’s performance. They demonstrate that active cooperation strategies have a greater bearing on performance in those firms whose primary customers are retailers. This circumstance provides evidence of the synergies and benefits that may arise when the supplier integrates the retailer in the supply chain, but which do not arise with other types of customers. Research limitations/implications – Although this study refers to a specific sector (fruits and vegetables) and the statistical results are limited, they provide insights that may assist in understanding how other perishable produce-related industries work: such industries share many common features. Practical implications – A more stable relationship between suppliers and retailers in the perishable produce market will render the supply firm more cooperative, competitive and profitable. Increased performance does not arise from the better conditions and improved sales power offered by the customer but instead from the adaptability of the supplier. Likewise, market diversification drives the supply firm toward a cooperative strategy, making it more profitable and competitive. As a practical norm, market diversification alone will not have positive results on performance unless the firm proves capable of enhancing its capacity for cooperation. Social implications – Proper management of the agricultural produce supply chain has repercussions on all of the members of that chain, although special emphasis should be placed on producers and consumers. The availability of food, its quality and its safety depend on management during the production phase. Along these lines, and more specifically for the consumer, this work is relevant because the sector analyzed accounts for 40 per cent of the vegetables consumed in Europe. Originality/value – This article defends the supplier–supplier relationship as the starting point for the analysis of a supply network. In certain sectors, the suppliers’ ability both to solve their clients’ problems and to be profitable is conditioned on maintaining the network and, therefore, the basic focus must center on analyzing their relationships, always including the customer, who has a direct or indirect influence on those relationships. Previous research has not comprehensively addressed this issue, let alone that of a sector with agile and perishable products in which, due to its nature, decision-making about market destinations and sales channels is the order of the day.

How can mixed integer linear programming assist dairy manufacturers by integrating supply decisions and production planning?

2021 ◽  
Vol 11 (2) ◽  
pp. 178-193
Author(s):  
Juliana Emidio ◽  
Rafael Lima ◽  
Camila Leal ◽  
Grasiele Madrona
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Dairy Products ◽  
Raw Milk ◽  
Mixed Integer ◽  
Content Type ◽  
Proposed Model ◽  
By Products

PurposeThe dairy industry needs to make important decisions regarding its supply chain. In a context with many available suppliers, deciding which of them will be part of the supply chain and deciding when to buy raw milk is key to the supply chain performance. This study aims to propose a mathematical model to support milk supply decisions. In addition to determining which producers should be chosen as suppliers, the model decides on a milk pickup schedule over a planning horizon. The model addresses production decisions, inventory, setup and the use of by-products generated in the raw milk processing.Design/methodology/approachThe model was formulated using mixed integer linear programming, tested with randomly generated instances of various sizes and solved using the Gurobi Solver. Instances were generated using parameters obtained from a company that manufactures dairy products to test the model in a more realistic scenario.FindingsThe results show that the proposed model can be solved with real-world sized instances in short computational times and yielding high quality results. Hence, companies can adopt this model to reduce transportation, production and inventory costs by supporting decision making throughout their supply chains.Originality/valueThe novelty of the proposed model stems from the ability to integrate milk pickup and production planning of dairy products, thus being more comprehensive than the models currently available in the literature. Additionally, the model also considers by-products, which can be used as inputs for other products.

Coordinating lot sizing and integrated production and distribution scheduling with batch delivery and holding cost

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maedeh Bank ◽  
Mohammad Mahdavi Mazdeh ◽  
Mahdi Heydari ◽  
Ebrahim Teimoury
Keyword(s):  
Supply Chain ◽  
Lot Sizing ◽  
Mixed Integer ◽  
Time Interval ◽  
Content Type ◽  
Integrated Production ◽  
Holding Costs ◽  
Integrated Production And Distribution ◽  
Distribution Scheduling ◽  
Production And Distribution

PurposeThe aim of this paper is to present a method for finding the optimum balance between sequence-dependent setup costs, holding costs, delivery costs and delay penalties in an integrated production–distribution system with lot sizing decisions.Design/methodology/approachTwo mixed integer linear programming models and an optimality property are proposed for the problem. Since the problem is NP-hard, a genetic algorithm reinforced with a heuristic is developed for solving the model in large-scale settings. The algorithm parameters are tuned using the Taguchi method.FindingsThe results obtained on randomly generated instances reveal a performance advantage for the proposed algorithm; it is shown that lot sizing can reduce the average cost of the supply chain up to 11.8%. Furthermore, the effects of different parameters and factors of the proposed model on supply chain costs are examined through a sensitivity analysis.Originality/valueAlthough integrated production and distribution scheduling in make-to-order industries has received a great deal of attention from researchers, most researchers in this area have treated each order as a job processed in an uninterrupted time interval, and no temporary holding costs are assumed. Even among the few studies where temporary holding costs are taken into consideration, none has examined the effect of splitting an order at the production stage (lot sizing) and the possibility of reducing costs through splitting. The present study is the first to take holding costs into consideration while incorporating lot sizing decisions in the operational production and distribution problem.

Survey of graduate supply chain courses: content, coverage and gaps

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Heather Lutz ◽  
Laura Birou ◽  
Joe Walden
Keyword(s):  
Higher Education ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Large Scale ◽  
Gap Analysis ◽  
Data Gathering ◽  
Graduate Courses ◽  
Chain Management ◽  
Content Type ◽  
Course Content

PurposeThis paper aims to provide the results of a survey of courses dedicated to the field of supply chain management in higher education. This research is unique because it represents the first large-scale study of graduate supply chain management courses taught at universities globally. Design/methodology/approachContent analysis was performed on each syllabus to identify the actual course content: requirements, pedagogy and content emphasis. This aggregated information was used to compare historical research findings in this area, with the current skills identified as important for career success. This data provides input for a gap analysis between offerings in higher education and those needs identified by practitioners. FindingsData gathering efforts yielded a sample of 112 graduate courses representing 61 schools across the world. The aggregate number of topics covered in graduate courses totaled 114. The primary evaluation techniques include exams, projects and homework. Details regarding content and assessment techniques are provided along with a gap analysis between the supply chain management course content and the needs identified by APICS Supply Chain Manager Competency Model (2014). Originality/valueThe goal is to use this data as a means of continuous improvement in the quality and value of the educational experience on a longitudinal basis. The findings are designed to foster information sharing and provide data for benchmarking efforts in the development of supply chain management courses and curricula in academia, as well as training, development and recruitment efforts by professionals in the field of supply chain management.

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