A multi-objective robust optimization model with defective vaccine and reverse supply chain under uncertainty

Pharmaceutical companies, upstream suppliers, associated logistics providers, health workers, regulatory agencies, public health experts and ultimately the medical practitioners and general public have been navigating an increasingly globalized vaccine supply chain; any disruption to the supply chain may cause cascading failure and have devastating consequences. The COVID-19 pandemic has already highlighted the lack of resilience in supply chains, as global networks fail from disruptions at single nodes and connections. As the race for a COVID-19 vaccine continues, the importance of not only an efficient supply chain but a resilient vaccine supply chain capable of reliable production and reaching target populations despite likely but currently unknown disruptions is imperative. Proactively applying resilience analytics to vaccine supply chain models will increase the probability that vaccination programs meet their goals. Without such a network in place for manufacture and distribution of the COVID-19 vaccine, even the most efficacious and safe vaccine will not prove viable. Through an overview of the existing vaccine and pharmaceutical supply chain publications focusing on resilience, as well as recent papers reporting modeling of resilience in supply chains across multiple fields, we find that models for supply chain resilience are few and most of them are focused on individual dimensions of resilience rather than on comprehensive strategy necessary for scaling up vaccine production and distribution in emergency settings. We find that COVID-19 resulted in a wave of interest to supply chain resilience, but publications from 2020 are narrow in focus and largely qualitative in nature; evidence-based models and measures are rare. Further, publications often focus exclusively on specific portions of the specific supply chain of interest, excluding associated supporting networks, such as transportation, social and command and control (C2) necessary for vaccine production and equitable distribution. This lack of network analysis is a major gap in the literature that needs to be bridged in order to create methods of real-time analysis and decision tools for the COVID-19 vaccine supply chain. We conclude that a comprehensive, quantitative approach to network resilience that encompasses the supply chain in the context of other social and physical networks is needed in order to address the emerging challenges of a large-scale COVID-19 vaccination program. We further find that the COVID-19 pandemic underscores the necessity of positioning supply chain resilience within a multi-network context and formally incorporating temporal dimensions into analysis through the NAS definition of resilience—plan, absorb, recover, adapt—to ensure essential needs are met across all dimensions of society. Modeling and analyzing vaccine supply chain resilience ensures that value is maintained should disruptions occur.KeywordsVaccine supply chain resilienceSupply chain resilienceVaccine supply chainPharmaceutical supply chainCOVID-19 supply chain

Zero waste strategy for green supply chain management with minimization of energy consumption

A capacity planning approach for sustainable-resilient supply chain network design under uncertainty: A case study of vaccine supply chain

Carbon emission is a concern across the industry due to its environmental impact. In order to reduce carbon emissions, industry have to look not only at their processes but also in the generation of emissions in the whole supply chain that it belongs to. This is more necessary when various forms of carbon emissions policies are faced by the industry. The current focus on research is either in the economics of supply chain or mainly on the forward or reverse supply chains when it pertains to the carbon emissions. However, as lifecycle of the product is also becoming important, the isolated treatment of supply chains should be avoided for an integrated (forward and reverse) supply chain, also called the closed loop supply chain (CLSC). The complexity arises when the supply chain is faced with different kind of carbon policies implemented by the governments, for example, carbon tax, carbon cap, and carbon-cap and tax. The design of CLSC may change with the change in the carbon emission policy. In this research, a stochastic model is developed for the design of a CLSC by considering carbon emission policies. This work is one of the first attempts to understand the implication of carbon emission policy on the design of a CLSC. The model is applied to a sample case of aluminum industry with a life cycle assessment of emission.Our preliminary findings include:(1) When the more scenarios are taken into account, the total cost and emission would increase, because more uncertain information is considered in CSSC design.(2) Given the same carbon cap, in a broad sense, the amount of emission credit traded in market changes in line with the total emission. It indicates that the emission trading is determined by the actual emission rather than the carbon price, even the uncertain carbon price is considered. However, a higher emission does not always lead to a bigger amount of emission to be traded.(3) The network structure obtained by the deterministic formulation is not able to be easily adapted to changes in demand and supply.(4) In order to deal with the uncertain demand, the CLSC has to enlarge its handling capacity by using the facilities with a higher capacity or incorporating more facilities with the same function. With the same purpose, the supplier selection decisions are also changed associate the increasing scenarios.(5) The fuel of diesel is selected regardless of the scenarios. It means the current carbon price level would not motivate the firms to gain profit or reduce costs by employing future fuels in transportation. This conclusion is also proved by the further investigation when the total cost and emission are observed under decreasing cap. A further investigation reveals the transportation mode doesn't change when the carbon price increase from 9 to 234. Consequently, the future fuels would be attractive to firms only when the transportation price reduced or other policy environment changes, such as government subsidy. The efforts in reducing the transportation cost with future fuels have never ceased and the advanced technologies in automobile industry provide opportunity for green transportation promoters.

Background: Since the roll-out of coronavirus disease 2019 (COVID-19) vaccines worldwide, South Africa has had to adjust and overcome challenges associated with the safe and effective distribution of COVID-19 vaccines to its citizens. Vaccines are biological products, and many supply chain factors could influence product integrity and efficacy. This study focuses on aiding the logistics industry in understanding the COVID-19 vaccine supply chain around its handling, storage, and transportation requirements.Objectives: The study had five objectives. Firstly, to understand the functionality and components of a vaccine supply chain and, secondly to identify the stakeholders involved and their roles. Thirdly, the researchers wanted to comprehend and clarify the cold chain protocols for each category of the COVID-19 vaccines procured and the appropriate international best practices. The last two objectives were to identify the skill and training requirements of stakeholders on all levels, and using these inputs in creating an educational toolkit, aimed at operationally involved supply chain stakeholders.Method: The researchers made use of both primary and secondary data, focusing mostly on collecting data through a literature review, stakeholder analysis, and interview process.Results: The study outcome was a COVID-19 vaccine educational toolkit with four tools addressing the research objectives: (1) An identification of all vaccine supply chain stakeholders, (2) vaccine categorisation according to type and equipment required, (3) handling, storage, and delivery protocols, and (4) vaccine supply chain skill and training requirements.Conclusion: These tools can be used as a basis when educating and/or training COVID-19 vaccine supply chain employees on different levels and stages.

Reverse Supply Chain Process as Environmental Sustainability in the Poultry Industry of Bangladesh

Attention to the reverse supply chain is increasing due to the increasing value of products and technologies at the end of the supply chain as well as the direct impact of new environmental legislation. Design strategies for reverse supply chains remain relatively unexplored and underdeveloped. Meanwhile, measuring supply chain performance has also become important as understanding, collaboration and integration have increased among supply chain members. It also helps companies to target profitable market segments or identify areas for improvement. Reverse supply chains are seen as one way to increase profits for companies. Company XYZ is a company that operates in recycling products from surrounding shops. This paper will focus on measuring reverse supply chain performance at XYZ recycling company. A simple general framework of the company will be presented as well as its mathematical model. This simple general model is considered applicable by small and medium businesses to optimize their reverse supply chain systems

Lots of manufacturer base their process planning on lean principles. A straight way of supply chain could use lean tools efficiently. What about reverse orientation of supply chains? Reverse logistics is one of the most remarkable pivot of reverse way supply chains. To form best and useable practices we may have should use proper lean tools. If it realizable at all... In my paper I ask for those conditions, elements, parts which are responsible for a well working reverse supply chain based on lean tool using systems. Which are the future effects if we use the proper lean tools? What are the consequences of a reverse supply chain works without lean tools.

Improving the sustainability of a reverse supply chain system under demand uncertainty by using postponement strategies.

Reverse supply chain (RSC) is an extension of the traditional supply chain (TSC) motivated by environmental requirements and economic incentives. TSC management deals with planning, executing, monitoring, and controlling a collection of organizations, activities, resources, people, technology, and information as the materials and products move from manufacturers to the consumers. Except for a short warranty period, TSC excludes most of the responsibilities toward the product beyond the point of sale. However, because of growing environmental awareness and regulations (e.g. product stewardship statute), TSC alone is no longer an adequate industrial practice. New regulations and public awareness have forced manufacturers to take responsibilities of products when they reach their end of lives. This has necessitated the creation of an infrastructure, known as RSC, which includes collection, transportation, and management of end-of-life products (EOLPs). The advantages of implementing RSC include the reduction in the use of virgin resources, the decrease in the materials sent to landfills and the cost savings stemming from the reuse of EOLPs, disassembled components, and recycled materials. TSC and RSC together represent a closed loop of materials flow. The whole system of organizations, activities, resources, people, technology, and information flowing in this closed loop is known as the closed-loop supply chain (CLSC). In RSC, the management of EOLPs includes cleaning, disassembly, sorting, inspecting, and recovery or disposal. The recovery could take several forms depending on the condition of EOLPs, namely, product recovery (refurbishing, remanufacturing, repairing), component recovery (cannibalization), and material recovery (recycling). However, neither the quality nor the quantity of returning EOLPs is predictable. This unpredictable nature of RSC is what makes its management challenging and necessitates innovative management science solutions to control it. In this chapter, we address the order-driven component and product recovery (ODCPR) problem for sensor-embedded products (SEPs) in an RSC. SEPs contain sensors and radio-frequency identification tags implanted in them at the time of their production to monitor their critical components throughout their lives. By facilitating data collection during product usage, these embedded sensors enable one to predict product/component failures and estimate the remaining life of components as the products reach their end of lives. In an ODCPR system, EOLPs are either cannibalized or refurbished. Refurbishment activities are carried out to meet the demand for products and may require reusable components. The purpose of cannibalization is to recover a limited number of reusable components for customers and internal use. Internal component demand stems from the component requirements in the refurbishment operation. It is assumed that the customers have specific remaining-life requirements on components and products. Therefore, the problem is to find the optimal subset and sequence of the EOLPs to cannibalize and refurbish so that (1) the remaining-life-based demands are satisfied while making sure that the necessary reusable components are extracted before attempting to refurbish an EOLP and (2) the total system cost is minimized. We show that the problem could be formulated as an integer nonlinear program. We then develop a hybrid genetic algorithm to solve the problem that is shown to provide excellent results. A numerical example is presented to illustrate the methodology.

Pharmaceutical industry supply chains: How to sustainably improve access to vaccines?

Sustainable supply chains are nowadays-targeted systems by both academics as well as industrial organizations. The Vaccines Supply Chain (VSC) being of utmost importance because of its great relevance in the world health, should be designed and operated in an optimized form not only aiming to guarantee high service levels at minimum costs but also considering environmental and social concerns. This study addresses such goal and proposes a Multi-Objective and multi-period Mixed Integer Linear Programming (MO-MILP) model for the simultaneous design and planning of sustainable VSC. The three dimensions of the Triple Bottom Line (TBL)—economic, environmental and social are modelled considering respectively the maximization of the Net Present Value (NPV); minimization of environmental impacts; and maximization of social impacts. The model is applied to a representative European supply chain case study, based in a European company. The outcomes obtained with the different scenarios studied clearly show how strategic and tactical decision-making impacts on key performance indicators in a VSC. Again, by the results, it becomes clear the existence of trade-offs between the sustainability dimensions considered and the importance of using multi-objective approach to find feasible and sustainable solutions.

ObjectivesThe design of the supply chain determines how effectively any vaccination campaign can be operated. This case study of Switzerland's vaccine supply chain compares its design with public health objectives. It maps the vaccine supply chain in Switzerland as it was set up to handle the first shipments of Covid-19 vaccine in 2021 to enable a more holistic view of supply and demand flows. Recommendations are made to improve emergency logistics of vaccines in the future.MethodsTwenty-six semi-structured interviews with international and Swiss stake-holders were coded and analyzed to arrive at a description of planning and distribution processes. The vaccine supply chain network structure was mapped, linking upstream and downstream flows of material and information. The visualization of nodes and flows was combined with spatial information, including population data. The results are summarized in narrative form to support decision-makers across disciplines.ResultsDespite adequate vaccine supply, abundant local endowments and high investment in infrastructure, the 2021 design of Switzerland's vaccine supply chain reduced the potential reach of target populations. The segmentation of catchment populations, collaboration between administrative units and better use of information on geolocation and material flows could have improved the speed and reach of vaccinations during the emergency response phase. Three recommendations are made for supply chain structures to support higher vaccination rates in the future.ConclusionsThe visualization identifies design alternatives which could have improved vaccination rates under the prevailing conditions. A supply chain map provides public health officials with a shared view of the vaccine supply chain in order to better match supply with demand. The case study contributes to developed country studies. In order to improve public health outcomes in Switzerland, investments to secure supply, strong national endowments, and excellent infrastructure must be combined with optimized supply chain design.

A multi-objective approach for designing a tire closed-loop supply chain network considering producer responsibility

Stochastic multi-objective models for network design problem