Food supply chain network robustness : a literature review and research agenda

Today’s business environment is characterized by challenges of strong global competition where companies tend to achieve leanness and maximum responsiveness. However, lean supply chain networks (SCNs) become more vulnerable to all kind of disruptions. Food SCNs have to become robust, i.e. they should be able to continue to function in the event of disruption as well as in normal business environment. Current literature provides no explicit clarification related to robustness issue in food SCN context. This paper explores the meaning of SCN robustness and highlights further research direction

Supply Chain Event Management System

The Supply Chain Management (SCM) can be defined as the set of proposals used to efficiently integrate suppliers, manufacturers and warehouses, such that the product is produced and distributed in the right quantity and at the right time, minimizing the total cost and satisfying the required service level (Simchi-Levi et al., 1999). To this aim, enterprises in a Supply Chain (SC) perform collaborative business processes (Soosay et al., 2008). Particularly, collaborative planning processes allow each enterprise to obtain production and/or distribution schedules synchronized with schedules of the other SC members (Derrouiche et al., 2008). In this chapter, a schedule is defined as a set of orders, where each order represents a supply process (production or distribution) that assigns materials to a place, states the required resources, the time period during which each resource is required and its required capacity. The execution of a schedule implies performing the operations defined in the supply process each order represents. As result of the uncertainty inherent in any supply process (Kleindorfer & Saad, 2005) disruptive events arise. The problems they cause during a schedule execution occur on a daily basis, and affect not only the organization where they are produced but also propagate throughout the SC (Lee et al., 1997; Radjou et al., 2002). That is, these disruptive events may affect the schedules and their synchronization. In this chapter a disruptive event is defined as a significant change in the order specifications or planned values of resource availability. These changes could be: rush or delay in the start or end date of the order, changes in the amount specified by the order, change in the expected future availability of a resource, and change into the current level of a resource regards to its planned value. They can be produced by changes that can take place into the enterprise or outside the enterprise. For example, an equipment breakdown, breakage of materials, change of material specification, weather conditions, traffic congestion, etc. The occurrence of disruptive events is a fact well known to the planning task, and therefore planning systems generate schedules including buffers (material, resource capacity and time) to be robust and flexible, thus the schedule can be adapted to conditions occurring during implementation (Van Landeghem & Vanmaele, 2002; Adhitya et al., 2007; Wang

Prioritization of petroleum supply chains’ disruption management strategies using combined framework of BSC approach, fuzzy AHP and fuzzy Choquet integral operator

Industries in every sector have observed tangible losses from a broad range of disruptions during recent years. Factors such as globalization and outsourcing have made supply chains more sophisticated and this makes disruption management more necessary. Any disruption in each part of supply chain makes the whole supply chain face derangement and at last, ultimate customers realize the shaped disadvantages. Since avoidance of disruption occurrence is not always possible, application of different strategies with the aid of minimization of negative effects seems necessary. That is why in this paper, different strategies for disruption management in petroleum products supply chain and suitable criteria for prioritizing them are recognized via Balanced Score Card approach measures. After that, by application of fuzzy Analytical Hierarchy Process and intuitionistic fuzzy Choquet integral operator, their priorities are specified in order to make a guideline for managers to set proper plans and manage such disruptions more accurately

Real-time information for disruption management in intermodal freight transport

This thesis focuses on the recovery phase after operational disruptions in intermodal freight transport, which is a vital aspect of mitigating impacts such as late deliveries and thus achieving high operational efficiency. Intermodal freight transport is influenced by the ongoing development of information and communication technologies. Real-time information from these technologies has been shown useful for managing disruptions at the operational level. Previous research on intermodal freight transport has focused on the effects of actions enabled by real-time information, which has generated a lack of understanding the importance of real-time information concerning the process that result in these actions, such as using real-time information to manage operational disruptions. In this thesis, the process of managing disruptions in the recovery phase by using real-time information to detect a disruption, predict its impacts and take suitable action is termed disruption management. The purpose of this thesis is to contribute to the understanding of the importance of real-time information for disruption management in intermodal freight transport. \ua0This thesis draws from a compilation of five studies conducted to examine various aspects of real-time information used during the recovery phase in different intermodal freight transport settings. The studies involved applying various methods used in qualitative case studies, such as interviews, observations, and a focus group, as well as a quantitative study involving discrete event simulation. The main results are as follows. First, the results identified how real-time information supports the phases of disruption management (i.e., detection, prediction and action) depending on different factors of real-time information. Second, connections between operational coordination regarding information and buffers are discussed in terms of how they influence the real-time information used for disruption management. Last, an investigation of the efficiency effects was made with different scenarios for real-time information regarding prediction of impact. Through these results, the thesis provides insights into the importance of real-time information for disruption management and theoretical contributions to intermodal freight transport by conceptualising the role of real-time information for disruption management at the operational level and its effects. The detailed descriptions of real-time information for recovery provides practical contributions for transport managers to understand and evaluate their processes at the recovery phase

Intelligent Operation System for the Autonomous Vehicle Fleet

Modular vehicles are vehicles with interchangeable substantial components also known as modules. Fleet modularity provides extra operational flexibility through on-field actions, in terms of vehicle assembly, disassembly, and reconfiguration (ADR). The ease of assembly and disassembly of modular vehicles enables them to achieve real-time fleet reconfiguration, which is proven as beneficial in promoting fleet adaptability and in saving ownership costs. The objective of military fleet operation is to satisfy uncertain demands on time while providing vehicle maintenance. To quantify the benefits and burdens from modularity in military operation, a decision support system is required to yield autonomously operation strategies for comparing the (near) optimal fleet performance for different vehicle architectures under diverse scenarios. The problem is challenging because: 1) fleet operation strategies are numerous, especially when modularity is considered; 2) operation actions are time-delayed and time-varying; 3) vehicle damages and demands are highly uncertain; 4) available capacity for ADR actions and vehicle repair is constrained. Finally, to explore advanced tactics enabled by fleet modularity, the competition between human-like and adversarial forces is required, where each force is capable to autonomously perceive and analyze field information, learn enemy's behavior, forecast enemy's actions, and prepare an operation plan accordingly. Currently, methodologies developed specifically for fleet competition are only valid for single type of resources and simple operation rules, which are impossible to implement in modular fleet operation. This dissertation focuses on a new general methodology to yield decisions in operating a fleet of autonomous military vehicles/robots in both conventional and modular architectures. First, a stochastic state space model is created to represent the changes in fleet dynamics caused by operation actions. Then, a stochastic model predictive control is customized to manage the system dynamics, which is capable of real-time decision making. Including modularity increases the complexity of fleet operation problem, a novel intelligent agent based model is proposed to ensure the computational efficiency and also imitate the collaborative decisions making process of human-like commanders. Operation decisions are distributed to several agents with distinct responsibility. Agents are designed in a specific way to collaboratively make and adjust decisions through selectively sharing information, reasoning the causality between events, and learning the other's behavior, which are achieved by real-time optimization and artificial intelligence techniques. To evaluate the impacts from fleet modularity, three operation problems are formulated: (i) simplified logistic mission scenario: operate a fleet to guarantee the readiness of vehicles at battlefields considering the stochasticity in inventory stocks and mission requirements; (ii) tactical mission scenario: deliver resources to battlefields with stochastic requirements of vehicle repairs and maintenance; (iii) attacker-defender game: satisfy the mission requirements with minimized losses caused by uncertain assaults from an enemy. The model is also implemented for a civilian application, namely the real-time management of reconfigurable manufacturing systems (RMSs). As the number of RMS configurations increases exponentially with the size of the line and demand changes frequently, two challenges emerge: how to efficiently select the optimal configuration given limited resources, and how to allocate resources among lines. According to the ideas in modular fleet operation, a new mathematical approach is presented for distributing the stochastic demands and exchanging machines or modules among lines (which are groups of machines) as a bidding process, and for adaptively configuring these lines and machines for the resulting shared demand under a limited inventory of configurable components.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147588/1/lixingyu_2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147588/2/lixingyu_1.pd

A model-based rescheduling framework for managing abnormal supply chain events

10.1016/j.compchemeng.2006.07.002Computers and Chemical Engineering315-6496-518CCEN

Recovery actions in freight transport through real-time disruption management

This thesis focuses on the management of disruption in freight transport. The management of disruption is of importance to achieve planned efficiency in the transport system by mitigating or avoiding the impacts of disruptions, such as late arrivals of deliveries. The transport system is influenced by the ongoing development of information and communication technologies, which makes real-time information related to the transport operations available. This information has been shown to be useful for disruption management and has created possibilities for a shift towards more autonomous transport systems. This thesis investigates the real-time disruption management, as the recovery phase of disruption at the operational level, using relevant information after a disruption has occurred. The studied literature has mainly considered this phase to be reactive and focused on recovery strategies as proactive actions before disruptions occur. This thesis considers proactive recovery actions as made after a disruption but before it impacts the transport chain. These kinds of recovery actions provide less impact from disruptions on the freight transport system than reactive recovery actions made after the impact has occurred do. The purpose of this research is to investigate real-time disruption management in freight transport, in order to generate possibilities for proactive recovery actions. Two cases of real-time disruption management have been investigated in this thesis, in three different studies. Each study examined different aspects regarding detection of disruptions, of what is detected, how it is detected and where in the transport system it is detected, influence on the initiation of real-time disruption management. The results from the performed studies point towards the importance of that detecting different objects of a disruption, which is further influenced by how and where in the system the detection is made. Furthermore, these insights into the detection phase are connected to the other phases for real-time disruption management, prediction and action, in order to state the possibilities of generating proactive recovery actions.In contrast to the developed literature of strategic recovery strategies, this thesis establishes a detailed description of the viewpoint of real-time management of disruptions. As the identified objects for detection in this research are shown to be represented by different information, it is valuable for the development of disruption management to match future autonomous parts of the transport system and develop decision support systems accordingly. Furthermore, the research contributes with two dimensions in which recovery actions can be viewed as proactive. This is generated either with real-time disruption management performed after impact but before impact on the transport system or after the impact on transport system but before impact on upcoming operations. The practical contribution includes concepts revolving around real-time disruption management, which can be used for an outline for needed information in order to generate possibilities for proactive recovery actions

Integrated management of chemical processes in a competitive environment

El objetivo general de esta Tesis es mejorar el proceso de la toma de decisiones en la gestión de cadenas de suministro, tomando en cuenta principalmente dos diferencias: ser competitivo considerando las decisiones propias de la cadena de suministro, y ser competitivo dentro de un entorno global. La estructura de ésta tesis se divide en 4 partes principales: La Parte I consiste en una introducción general de los temas cubiertos en esta Tesis (Capítulo 1). Una revisión de la literatura, que nos permite identificar las problemáticas asociadas al proceso de toma de decisiones (Capítulo 2). El Capítulo 3 presenta una introducción de las técnicas y métodos de optimización utilizados para resolver los problemas propuestos en esta Tesis. La Parte II se enfoca en la integración de los niveles de decisión, buscando mejorar la toma de decisiones de la propia cadena de suministro. El Capítulo 4 presenta una formulación matemática que integra las decisiones de síntesis de procesos y las decisiones operacionales. Además, este capítulo presenta un modelo integrado para la toma de decisiones operacionales incluyendo las características del control de procesos. El Capítulo 5 muestra la integración de las decisiones del nivel táctico y el operacional, dicha propuesta está basada en el conocimiento adquirido capturando la información relacionada al nivel operacional. Una vez obtenida esta información se incluye en la toma de decisiones a nivel táctico. Finalmente en el capítulo 6 se desarrolla un modelo simplificado para integrar múltiples cadenas de suministro. El modelo propuesto incluye la información detallada de las entidades presentes en una cadena de suministro (suministradores, plantas de producción, distribuidores y mercados) introduciéndola en un modelo matemático para su coordinación. La Parte III propone la integración explicita de múltiples cadenas de suministro que tienen que enfrentar numerosas situaciones propias de un mercado global. Asimismo, esta parte presenta una nueva herramienta de optimización basada en el uso integrado de métodos de programación matemática y conceptos relacionados a la Teoría de Juegos. En el Capítulo 7 analiza múltiples cadenas de suministro que cooperan o compiten por la demanda global del mercado. El Capítulo 8 incluye una comparación entre el problema resuelto en el Capítulo anterior y un modelo estocástico, los resultados obtenidos nos permiten situar el comportamiento de los competidores como fuente exógena de la incertidumbre típicamente asociada la demanda del mercado. Además, los resultados de ambos Capítulos muestran una mejora sustancial en el coste total de las cadenas de suministro asociada al hecho de cooperar para atender de forma conjunta la demanda disponible. Es por esto, que el Capítulo 9 presenta una nueva herramienta de negociación, basada en la resolución del mismo problema (Capítulo 7) bajo un análisis multiobjetivo. Finalmente, la parte IV presenta las conclusiones finales y una descripción general del trabajo futuro.This Thesis aims to enhance the decision making process in the SCM, remarking the difference between optimizing the SC to be competitive by its own, and to be competitive in a global market in cooperative and competitive environments. The structure of this work has been divided in four main parts: Part I: consists in a general introduction of the main topics covered in this manuscript (Chapter I); a review of the State of the Art that allows us to identify new open issues in the PSE (Chapter 2). Finally, Chapter 3 introduces the main optimization techniques and methods used in this contribution. Part II focuses on the integration of decision making levels in order to improve the decision making of a single SC: Chapter 4 presents a novel formulation to integrate synthesis and scheduling decision making models, additionally, this chapter also shows an integrated operational and control decision making model for distributed generations systems (EGS). Chapter 5 shows the integration of tactical and operational decision making levels. In this chapter a knowledge based approach has been developed capturing the information related to the operational decision making level. Then, this information has been included in the tactical decision making model. In Chapter 6 a simplified approach for integrated SCs is developed, the detailed information of the typical production‐distribution SC echelons has been introduced in a coordinated SC model. Part III proposes the explicit integration of several SC’s decision making in order to face several real market situations. As well, a novel formulation is developed using an MILP model and Game Theory (GT) as a decision making tool. Chapter 7 includes the tactical and operational analysis of several SC’s cooperating or competing for the global market demand. Moreover, Chapter 8 includes a comparison, based on the previous results (MILP‐GT optimization tool) and a two stage stochastic optimization model. Results from both Chapters show how cooperating for the global demand represent an improvement of the overall total cost. Consequently, Chapter 9 presents a bargaining tool obtained by the Multiobjective (MO) resolution of the model presented in Chapter 7. Finally, final conclusions and further work have been provided in Part IV.Postprint (published version

Development of model for logistics risk management in supply chains

Doktorska disertacija razmatra probleme upravljanja rizicima u lancima snabdevanja sa osnovnim ciljem razvoja modela za upravljanje određenom grupom rizika-logističkim rizicima. Na osnovu širokog pregleda postojeće literature predloženo je više originalnih konceptualnih okvira namenjenih razumevanju složene strukture koncepta rizika u lancima snabdevanja i principa njihove sistemske analize i upravljanja. Takođe, razvijen je originalni model identifikacije, ocene i tretiranja logističkih rizika, koji se zasniva na simulaciji diskretnih događaja i SCOR metodologiji. Testiranjem predloženih okvira i modela na realnom primeru pokazana je njihova praktična primeljivost.The thesis is dedicated to exploring the problems of supply chain risk management with the final aim of developing model for logistics risk management. Based on a broad literature review it is proposed a several original conceptual frameworks aimed to understanding the complex structure of the supply chain risks concept as well as principles of their system analysis and management. In addition, original model for identification, assessment and control is developed, based on discrete event simulation and SCOR methodology. Case study shows practical applicability of proposed frameworks and models