A solution method for a two-layer sustainable supply chain distribution model

This article presents an effective solution method for a two-layer, NP-hard sustainable supply chain distribution model. A DoE-guided MOGA-II optimiser based solution method is proposed for locating a set of non-dominated solutions distributed along the Pareto frontier. The solution method allows decision-makers to prioritise the realistic solutions, while focusing on alternate transportation scenarios. The solution method has been implemented for the case of an Irish dairy processing industry׳s two-layer supply chain network. The DoE generates 6100 real feasible solutions after 100 generations of the MOGA-II optimiser which are then refined using statistical experimentation. As the decision-maker is presented with a choice of several distribution routes on the demand side of the two-layer network, TOPSIS is applied to rank the set of non-dominated solutions thus facilitating the selection of the best sustainable distribution route. The solution method characterises the Pareto solutions from disparate scenarios through numerical and statistical experimentations. A set of realistic routes from plants to consumers is derived and mapped which minimises total CO2 emissions and costs where it can be seen that the solution method outperforms existing solution methods

Road-based goods transportation : a survey of real-world logistics applications from 2000 to 2015

The vehicle routing problem has been widely studied from a technical point of view for more than 50 years. Many of its variants are rooted in practical settings. This paper provides a survey of the main real-life applications of road-based goods transportation over the past 15 years. It reviews papers in the areas of oil, gas and fuel transportation, retail, waste collection and management, mail and package delivery and food distribution. Some perspectives on future research and applications are discussed

A review on energy supply chain resilience through optimization

The concept of supply chain resilience continues to attract both industry and research experts in the field of energy. These stakeholders continue to tackle disruptions to supply chain systems through the introduction of strategy options for resilience. A better understanding of broader dimensions of potential disruptions to supply chains caused by uncertainties has become eminent, especially as currently experienced during the global COVID-19 pandemic. The effects of the outbreak in disrupting supply chains in the energy sector will, in the next decade, continue to be a likely concern for industry and research stakeholders. Balancing the increasing need for energy security to meet the continuous growth in energy demand through shortage reduction and increased uptime using optimization is the core of this research. This review paper provides an insight into recent studies in the field of natural gas supply chain resilience as a major player in the energy mix, and the continued disruption and subsequent shutdowns of plant nodes, which results in emission loss to the environment. This paper is motivated by the disparity between demand and supply triggered by the disruption of supply chain networks. Referenced in this paper are scientific work on supply chain resilience of biomass, water, power systems, and natural gas. Findings show that existing studies favor fewer system-based strategies in optimizing for resilience. This review concludes that an optimization is a useful tool to continuously achieve resilience in supply chain production, storage, and transportation activities

An (R,S)-Inventory Policy for Winter Maintenance Materials for the State of Ohio

Winters in Ohio mean snow and ice, and with snow and ice come treacherous roads. Roads that become treacherous or impassable cost the state economically and socially. Thus to prevent this from happening road crews are out spreading salt on the roads before, during, and after a storm to promote safe travel. To provide the amount of salt needed to all counties of Ohio; individual counties stock up during the summer and fall, re-order to maintain inventory through the winter time, and finally allowing inventories to reduce towards the end of winter. During a mild winter salt not used and left in inventory ties up capital and requires the county to hold the salt until the next winter at a cost. An (R,S)-inventory policy was constructed to match salt inventories more closely with the demand in each Ohio county. The new salt ordering policies tie current decisions making to historical usage, and result in lower inventory levels in the simulation results, while maintaining required levels of service. The parameters for the inventory policy are derived using a demand model based on a linear regression model. The demand model was used to match past usage from 7 winter seasons with weather variables to calculate predictions of salt usage. A second method allows the inventory policy to be derived directly from the usage data when weather data is unavailable. A simulation approach was used to test the effectiveness of the policies and to establish several parameters in the implementation of the policies

Integrated supply chain design using multi criteria mixed integer programming.

This research focuses on following key Supply Chain Design questions: determining supplier selection, production quantities, inventory locations and sizes, transportation option selection and transportation quantity in a multi stage, multi level supply chain. A Novel Integrated Supply Chain Design Framework that integrates Production Costs, Transportation Costs, First Time Quality and Supplier On-Time Delivery criteria has been proposed and implemented. Mixed Integer Linear Programming models were developed and four classes of problems were solved. Real world automotive industry data was used for testing and verifying these models. Key new knowledge, both data dependent and data independent, was gained in the course of this research. Data dependent insights include: (1) Recommendation for splitting the customer demand between two suppliers even in the absence of capacity constraints, and (2) Unit Production Cost, Unit Transportation Cost and FTQ were shown to be the most critical factors in the Total Global Supply Chain Costs. Data independent insights indicated that: (1) Supplier selection decisions at every stage and level should be made using a global integrated approach of considering both production and transportation costs across the complete supply chain avoiding the myopic approach of always looking for the cheapest part from the lowest bidding supplier, (2) Out-sourcing to a non-domestic, less expensive supplier is not always the best decision for every product when selecting suppliers, (3) The Total Global Supply Chain Costs, Production Costs and Transportation Costs all increase non-linearly with worsening FTQ of the Supply Chain links, and (4) Supplier FTQ has the most severe impact on the supply chain stage farthest from the Demand Consumption Stage with the impact severity being higher at lower FTQ rates. This research has clearly demonstrated the merits and benefits of taking an integrated decision making approach when selecting suppliers. A multi-criteria model that combines the cost of production, transportation, first-time quality and supplier on-time delivery has been proposed and tested. Significant savings can be achieved as a result of using the framework developed in this research. The savings in the total supply chain cost, in the automotive example used for illustration, were in excess of 15% which translates into several Million dollars over a period of 3 Years.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .M353. Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1110. Adviser: Hoda A. Elmaraghy. Thesis (Ph.D.)--University of Windsor (Canada), 2004

Optimisation of energy supply chains considering sustainability aspects

The supply chain of energy sources and, in particular, natural gas is prone to endogenous and exogenous disruptions that affect the system’s operational performance and flow capacity, thereby contributing to greenhouse gases (GHG) through methane (CH4) emissions. Although there are operational strategies to improve the gas supply chain, the need for resilience-driven optimisation that provides a system-based workflow to mitigate continuous and prolonged disruptions in the midstream remains crucial. This study focuses on developing a novel optimisation model that investigates the potential of a complementary design in the natural gas supply chain as a mitigation approach, enhancing throughput delivery without disconnections, and exploring the potential retrofit benefits of an existing natural gas supply chain infrastructure. To achieve this, optimisation in the supply chain’s transmission echelon is deployed to increase flexibility capacity, reduce gas losses, and minimise emissions. In this study, a lateral relief pipeline in the transmission node is proposed as an alternative pathway for gas flow to increase the resilience of the supply chain. This proposed strategy transmits excess trapped gas between inlet and outlet nodes during plant shutdowns within operational and contractual constraints. This redundancy compensates for downtime and pressure drop caused by shutdowns of system nodes during disruptions. The objective of the optimisation problem is to maximise throughput through flow flexibility and minimise carbon dioxide (CO2) emissions through a reduction in gas losses. Different scenarios are introduced to achieve the objective function optimum. Firstly, the baseline scenario (BS) of the system’s status is analysed under normal conditions to identify the flow rate gap. Then the disruption scenario (DS) is introduced where the impact of the lateral relief pipeline to mitigate unplanned shutdowns is analysed by using defined parameters in a steady state (SS). With a fixed shutdown period, the variation in plant node performance is examined at different flow rates. Lastly, in a transient state (TS), the pressure variation between the inlet and the outlet nodes in the mainline and when the relief pipeline node is opened is investigated. All scenarios affect the supply chain’s overall performance; therefore, the resulting flow rates are compared for optimum decision making. A multi-stream, multi-period, single-product transmission model to satisfy consumer demand within a given time frame is developed for the simulation, formulated as a mixed-integer linear programming (MILP) model, and applied within an optimisation framework where interruptions to the supply chain are studied to optimise the strategic planning problem. The optimisation procedure is formulated in a deterministic environment, and the model is run using General Algebraic Modelling System (GAMS) 26.14 with the CPLEX solver 12 in an intel ® core ™ i7 and a zerooptimality gap. Data collected from gas companies in the case study country are analysed and used to forecast and calculate the gas flow rate and the required capacity to meet growing demand. The data accessed enhance the applicability of the proposed model. Also, the interactions between the nodes in the supply chain are adjusted to mitigate interruptions and increase overall efficiency. Furthermore, an economic analysis of the proposed complementary design is carried out to ascertain possible tradeoffs between costs and resilience. Finally, a sensitivity analysis is conducted to assess the impact of key parameters on the overall model’s prediction

Automotive Supply Chain Auswertung mit herkömmlichem Modell und integriertem Modell

ABSTRACT: Increasing competition due to market globalization, product diversity and technological breakthroughs stimulates independent automotive companies to collaborate in a supply chain that allows them to gain mutual benefits. Especially the events of the past years have shell-shocked even the most ardent industry participants – a crisis and the following hard recovery. Not only the critical challenges in implementing process lean with low cost and high quality, also critical to success is the ability to efficiently meet stricter emissions and fuel economy standards escalating in most jurisdictions. With all the factors working beneath the waves, supply chain management becomes the core source of a company’s competitive advantages and even the trump of the entire automotive industry’s success. A proper supply chain strategy provides financial returns and other key factors superior to the old concepts which brought profits before but no longer up to date now. Correctly design and effectively evaluate the supply chains, and improve the supply chain structure dynamically over time, are the key methods for an automotive company to survive and succeed in the volatile and critical automobile industrial environment. In this research work, based on the real case study in the automotive door system supply, different supply chain scenarios are designed and corresponding performance evaluations are made by applying different methods, namely the conventional model and the integrated model with their corresponding algorithms. With conventional model, the evaluation is done from different aspects, where the chosen perspectives such as costs, flexibility, stability, and reliability are assessed respectively for the multi-stage international supply chains. The data applied in this model comes from real-case door module supply, and the evaluation results helps in the decision making in localization process of that certain project. To be able to evaluate more complicated supply chain scenarios in a more accurate and efficient way, an integrated model is designed for the comprehensive performance evaluation. Based on the fuzzy theory, a MDFIE (Multilevel Dynamic Fuzzy Integrated Evaluation) algorithm is developed to assess the automotive supply chain performance. With the real case of vehicle door system supply, a detailed index system is designed based on a profound understanding of the automotive door supply chain. And with this new method, supply chain scenarios with different outsource degree and integration degree are evaluated and analyzed, a positive solution of deeper integration and downstream task shifting in the automotive supply structure is concluded in the end. In addition to the use in this research work, the integrated model, especially the index system can be flexibly adjusted for other automotive supply chains under their special interest and requirements. And with the MDFIE algorithm or other possible methods, the model can also be further developed into user-friendly software or system for the normal application. This software development is suggested for the further research. Based on the researches done in this work, a new tier structure is proposed as well. A mega system supplier which is defined as the new Tier 0,5 and other outsourced service companies which are playing as the half tiers (tier 1,5/ 2,5…) are discussed in this work. With all the theoretical researches and practical investigations, this new structure which occupies the niche positions of supply chain is supposed to be benefiting the entire automotive supply chain in many critical aspects, like the long lasting over capacity problem and the coming E-mobility trend. Some other suggestions like the application of RFID technology are also proposed for increasing the productivity and strengthen the information flow along supply chain. In general, improving the entire automotive supply chain performance, is the ultimate goal of supply chain management, which means balancing all participators’ maximum profits and offering the highest market service level. The realization of the proposals and concepts, is also supposed to be studied in the further research.ZUSAMENFASSUNG: Die strengeren Emissions- und Kraftstoffverbrauchstandards effizient zu erfüllen, spielt neben der kritischen Herausforderungen bei der Umsetzung „Lean Prozess“ mit niedrigen Kosten und hoher Qualität für den Erfolg auch eine entscheidende Rolle. Der zunehmende Wettbewerb infolge der Globalisierung der Märkte, der Produktvielfalt und technologischer Durchbrüche stimuliert die Zusammenarbeit von unabhängiger Automobileunternehmen. Insbesondre in den letzten Jahren wurden die Teilnehmer aus dem Industriebranche von der Krise und dessen nachstehender Erholung schockiert. Mit allen Faktoren unter den Wellen bleibt das Supply-Chain-Management die Hauptquelle für die Wettbewerbsvorteile eines Unternehmens und überhaupt der Trumpf des Erfolgs in der gesamten Automobilindustrie. Eine richtige Supply Chain-Strategie bietet finanzielle Erträge und andere wichtige Faktoren, die besser als die alten Konzepte sind. Richtiges Design und gewissenhaftes Abschätzen des Supply Chains, und im Laufe der Zeit die Supply-Chain-Struktur dynamisch zu Verbessern sind die Schlüssel-Methoden für ein Automobilunternehmen, um in dem unberechenbaren und kritischen Automobilindustrieumfeld zu überleben und erfolgreich zu bleiben. Diese Arbeit basiert auf der realen Fallstudien der Türsystemlieferung in der Automobilindustrie. Verschiedene Supply Chain Szenarien werden entworfen und die entsprechenden Leistungen werden durch Anwendung unterschiedlicher Methoden bewertet, und zwar das herkömmlichen Modell und das integrierte Modell mit den entsprechenden Algorithmen. Beim herkömmlichen Modell wird unter verschiedenen Aspekten bewertet, wobei die gewählten Perspektiven wie Kosten, Flexibilität, Stabilität und Zuverlässigkeit jeweils für die mehrstufigen internationalen Lieferketten bewertet werden. Die genommenen Daten in diesem Modell stammen aus den Fällen von Türmodul - Auslieferung. Die Bewertungsergebnisse sind beim Entscheidungstreffen im Lokalisierungsprozess des gewissen Projektes hilfreich. Um die komplizierter Supply Chain Szenarien in einer genaueren und effizienteren Methode bewerten zu können, wird ein integriertes Modell für die umfassenden Leistungsbewertung gebaut. Auf der Basis von Fuzzy-Theorie, wird ein MDFIE (Multilevel Dynamische Fuzzy Integrierte Evaluation) Algorithmus entwickelt. Anhand der realen Auslieferungsfälle im Fahrzeugtürensystem wird ein detailliertes Index-System ausgelegt, welches auf einem tiefen Verständnis der Automotive Supply Chain basiert. Mit dieser neuen Methode werden Supply-Chain-Szenarien durch unterschiedliche Outsourcengrade und Integrationsgrade ausgewertet und analysiert. Eine positive Lösung von der vertiefen Integration und von der nachgeordneten Aufgabenumlagerung in der Automobilzuliefer-Struktur wird am Ende kristallisiert. Zusätzlich zu dem Einsatz in dieser Arbeit kann das integrierte Modell, vor allem das Index-System flexibel für andere Wertschöpfungsketten ihrer besonderen Interessen und Bedürfnissen entsprechend angepasst werden. Und mit dem MDFIE Algorithmus oder andere mögliche Methoden kann das Modell auch in einer benutzerfreundlichen Software oder System für die normale Anwendung integriert und entwickelt werden. Diese Software-Entwicklung wird für die weitere Forschung vorgeschlagen. Basierend auf den Untersuchungen in dieser Arbeit wird eine neue Stufenstruktur auch vorgeschlagen. Ein Mega-Systemzulieferer, die sogenannt neues Tier 0,5 ist, und ausgelagerter Service-Unternehmen, die als Hälfte Tiers (Tier 1,5 / 2,5 ...) definiert werden, sind in dieser Arbeit diskutiert. Mit theoretischen und praktischen Forschungen soll diese neue Struktur, deren Nische Positionen der Supply Chain beschäftigt sind, zu Gunsten der gesamten automobilen Wertschöpfungskette in vielen kritischen Aspekten bringen, z.B. das Überkapazitätsproblem und der kommende E-Mobilität Trend. Einige andere Vorschläge wie die Anwendung der RFID-Technologie zur Steigerung der Produktivität und zur Stärkung der Informationsfluss entlang der Lieferkette wird auch gemacht. Das ultimative Ziel des Supply-Chain- Managemenes ist die allgemeine Verbesserung der gesamten automobilen Wertschöpfungskettenleistung, die die maximale Gewinne von allen Teilnehmern zur Balancierung und den höchsten Market-Service-Level bedeutet. Die Realisierung der Vorschläge und Konzepte soll auch in der weiteren Forschung untersucht werden