Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach

© 2017, Springer Science+Business Media, LLC. Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation

Development of transportation and supply chain problems with the combination of agent-based simulation and network optimization

Demand drives a different range of supply chain and logistics location decisions, and agent-based modeling (ABM) introduces innovative solutions to address supply chain and logistics problems. This dissertation focuses on an agent-based and network optimization approach to resolve those problems and features three research projects that cover prevalent supply chain management and logistics problems. The first case study evaluates demographic densities in Norway, Finland, and Sweden, and covers how distribution center (DC) locations can be established using a minimizing trip distance approach. Furthermore, traveling time maps are developed for each scenario. In addition, the Nordic area consisting of those three countries is analyzed and five DC location optimization results are presented. The second case study introduces transportation cost modelling in the process of collecting tree logs from several districts and transporting them to the nearest collection point. This research project presents agent-based modelling (ABM) that incorporates comprehensively the key elements of the pick-up and delivery supply chain model and designs the components as autonomous agents communicating with each other. The modelling merges various components such as GIS routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. The entire pick-up and delivery operation are modeled by ABM and modeling outcomes are provided by time series charts such as the number of trucks in use, facilities inventory and travel distance. In addition, various scenarios of simulation based on potential facility locations and truck numbers are evaluated and the optimal facility location and fleet size are identified. In the third case study, an agent-based modeling strategy is used to address the problem of vehicle scheduling and fleet optimization. The solution method is employed to data from a real-world organization, and a set of key performance indicators are created to assess the resolution's effectiveness. The ABM method, contrary to other modeling approaches, is a fully customized method that can incorporate extensively various processes and elements. ABM applying the autonomous agent concept can integrate various components that exist in the complex supply chain and create a similar system to assess the supply chain efficiency.Tuotteiden kysyntä ohjaa erilaisia toimitusketju- ja logistiikkasijaintipäätöksiä, ja agenttipohjainen mallinnusmenetelmä (ABM) tuo innovatiivisia ratkaisuja toimitusketjun ja logistiikan ongelmien ratkaisemiseen. Tämä väitöskirja keskittyy agenttipohjaiseen mallinnusmenetelmään ja verkon optimointiin tällaisten ongelmien ratkaisemiseksi, ja sisältää kolme tapaustutkimusta, jotka voidaan luokitella kuuluvan yleisiin toimitusketjun hallinta- ja logistiikkaongelmiin. Ensimmäinen tapaustutkimus esittelee kuinka käyttämällä väestötiheyksiä Norjassa, Suomessa ja Ruotsissa voidaan määrittää strategioita jakelukeskusten (DC) sijaintiin käyttämällä matkan etäisyyden minimoimista. Kullekin skenaariolle kehitetään matka-aikakartat. Lisäksi analysoidaan näistä kolmesta maasta koostuvaa pohjoismaista aluetta ja esitetään viisi mahdollista sijaintia optimointituloksena. Toinen tapaustutkimus esittelee kuljetuskustannusmallintamisen prosessissa, jossa puutavaraa kerätään useilta alueilta ja kuljetetaan lähimpään keräyspisteeseen. Tämä tutkimusprojekti esittelee agenttipohjaista mallinnusta (ABM), joka yhdistää kattavasti noudon ja toimituksen toimitusketjumallin keskeiset elementit ja suunnittelee komponentit keskenään kommunikoiviksi autonomisiksi agenteiksi. Mallinnuksessa yhdistetään erilaisia komponentteja, kuten GIS-reititys, mahdolliset tilojen sijainnit, satunnaiset puunhakupaikat, kaluston mitoitus, matkan pituus sekä monimuotokuljetukset. ABM:n avulla mallinnetaan noutojen ja toimituksien koko ketju ja tuloksena saadaan aikasarjoja kuvaamaan käytössä olevat kuorma-autot, sekä varastomäärät ja ajetut matkat. Lisäksi arvioidaan erilaisia simuloinnin skenaarioita mahdollisten laitosten sijainnista ja kuorma-autojen lukumäärästä sekä tunnistetaan optimaalinen toimipisteen sijainti ja tarvittava autojen määrä. Kolmannessa tapaustutkimuksessa agenttipohjaista mallinnusstrategiaa käytetään ratkaisemaan ajoneuvojen aikataulujen ja kaluston optimoinnin ongelma. Ratkaisumenetelmää käytetään dataan, joka on peräisin todellisesta organisaatiosta, ja ratkaisun tehokkuuden arvioimiseksi luodaan lukuisia keskeisiä suorituskykyindikaattoreita. ABM-menetelmä, toisin kuin monet muut mallintamismenetelmät, on täysin räätälöitävissä oleva menetelmä, joka voi sisältää laajasti erilaisia prosesseja ja elementtejä. Autonomisia agentteja soveltava ABM voi integroida erilaisia komponentteja, jotka ovat olemassa monimutkaisessa toimitusketjussa ja luoda vastaavan järjestelmän toimitusketjun tehokkuuden arvioimiseksi yksityiskohtaisesti.fi=vertaisarvioitu|en=peerReviewed

Disruption Response Support For Inland Waterway Transportation

Motivated by the critical role of the inland waterways in the United States\u27 transportation system, this dissertation research focuses on pre- and post- disruption response support when the inland waterway navigation system is disrupted by a natural or manmade event. Following a comprehensive literature review, four research contributions are achieved. The first research contribution formulates and solves a cargo prioritization and terminal allocation problem (CPTAP) that minimizes total value loss of the disrupted barge cargoes on the inland waterway transportation system. It is tailored for maritime transportation stakeholders whose disaster response plans seek to mitigate negative economic and societal impacts. A genetic algorithm (GA)-based heuristic is developed and tested to solve realistically-sized instances of CPTAP. The second research contribution develops and examines a tabu search (TS) heuristic as an improved solution approach to CPTAP. Different from GA\u27s population search approach, the TS heuristic uses the local search to find improved solutions to CPTAP in less computation time. The third research contribution assesses cargo value decreasing rates (CVDRs) through a Value-focused Thinking based methodology. The CVDR is a vital parameter to the general cargo prioritization modeling as well as specifically for the CPTAP model for inland waterways developed here. The fourth research contribution develops a multi-attribute decision model based on the Analytic Hierarchy Process that integrates tangible and intangible factors in prioritizing cargo after an inland waterway disruption. This contribution allows for consideration of subjective, qualitative attributes in addition to the pure quantitative CPTAP approach explored in the first two research contributions

El problema de localización y ruteo con múltiples objetivos: una revisión de literatura

Contexto: El problema de localización y ruteo constituye una de las principales temáticas en el área de logística e investigación de operaciones con un enfoque hacia la minimización de los costos totales del sistema. Sin embargo, en la gestión de la cadena de suministro, que actualmente presenta una tendencia hacia la sostenibilidad, la mayoría de las decisiones involucra la optimización simultánea de diversos objetivos, incluyendo perspectivas económicas, sociales y ambientales, de lo cual surge el problema de localización y ruteo con múltiples objetivos. Método: Se realiza una revisión sistemática de la literatura sobre el problema de localización y ruteo con múltiples objetivos, consultando las bases de datos Scopus y Web of Science. De acuerdo con unos criterios de selección específicos, se identifican 99 artículos científicos asociados a la temática durante el periodo comprendido entre 1989 y 2022, los cuales se clasifican según el tipo de aplicación. Resultados: Se describen las características más importantes para cada una de las aplicaciones del problema de localización y ruteo con múltiples objetivos en la literatura y se realiza una revisión de las investigaciones según sus objetivos de estudio y métodos de solución, para finalmente identificar las oportunidades de investigación principales. Conclusiones: En primer lugar, la mayoría de los estudios sobre el problema de localización y ruteo multiobjetivo han estudiado la gestión de residuos, la distribución de elementos de socorro, los productos perecederos, el problema de localización y ruteo verde, la cadena de frío y la distribución de bebidas. El objetivo de optimización de mayor implementación es la minimización de costos, combinado con otros objetivos: minimización de riesgos, impactos ambientales, minimización de tiempo, maximización de la satisfacción del cliente, balance de carga de trabajo y confiabilidad rutas. Por otra parte, se aplican métodos exactos y aproximados multiobjetivo para dar solución al problema, siendo los algoritmos evolutivos los más usados para modelos de mayor complejidad. Finalmente, las investigaciones actuales están orientadas al desarrollo de modelos bajo condiciones de incertidumbre y estocásticos, múltiples periodos, ventanas de tiempo, múltiples escalones y flota heterogénea.Contexto: El problema de localización y ruteo constituye una de las principales temáticas en el área de logística e investigación de operaciones con un enfoque hacia la minimización de los costos totales del sistema. Sin embargo, en la gestión de la cadena de suministro, que actualmente presenta una tendencia hacia la sostenibilidad, la mayoría de las decisiones involucra la optimización simultánea de diversos objetivos, incluyendo perspectivas económicas, sociales y ambientales, de lo cual surge el problema de localización y ruteo con múltiples objetivos. Método: Se realiza una revisión sistemática de la literatura sobre el problema de localización y ruteo con múltiples objetivos, consultando las bases de datos Scopus y Web of Science. De acuerdo con unos criterios de selección específicos, se identifican 99 artículos científicos asociados a la temática durante el periodo comprendido entre 1989 y 2022, los cuales se clasifican según el tipo de aplicación. Resultados: Se describen las características más importantes para cada una de las aplicaciones del problema de localización y ruteo con múltiples objetivos en la literatura y se realiza una revisión de las investigaciones según sus objetivos de estudio y métodos de solución, para finalmente identificar las oportunidades de investigación principales. Conclusiones: En primer lugar, la mayoría de los estudios sobre el problema de localización y ruteo multiobjetivo han estudiado la gestión de residuos, la distribución de elementos de socorro, los productos perecederos, el problema de localización y ruteo verde, la cadena de frío y la distribución de bebidas. El objetivo de optimización de mayor implementación es la minimización de costos, combinado con otros objetivos: minimización de riesgos, impactos ambientales, minimización de tiempo, maximización de la satisfacción del cliente, balance de carga de trabajo y confiabilidad rutas. Por otra parte, se aplican métodos exactos y aproximados multiobjetivo para dar solución al problema, siendo los algoritmos evolutivos los más usados para modelos de mayor complejidad. Finalmente, las investigaciones actuales están orientadas al desarrollo de modelos bajo condiciones de incertidumbre y estocásticos, múltiples periodos, ventanas de tiempo, múltiples escalones y flota heterogénea

A multimodal network flow problem with product quality preservation, transshipment, and asset management

In this paper, we present an optimization model for a transportation planning problem with multiple transportation modes, highly perishable products, demand and supply dynamics, and management of the reusable transport units (RTIs). Such a problem arises in the European horticultural chain, for example. As a result of geographic dispersion of production and market, a reliable transportation solutions ensures long-term success in the European market. The model is an extension to the network ow problem. We integrate dynamic allocation, ow, and repositioning of the RTIs in order to nd the trade-o between quality requirements and operational considerations and costs. We also present detailed computational results and analysis

Pre-positioning of relief items under road/facility vulnerability with concurrent restoration and relief transportation

Planning for response to sudden-onset disasters such as earthquakes, hurricanes, or floods needs to take into account the inherent uncertainties regarding the disaster and its impacts on the affected people as well as the logistics network. This article focuses on the design of a multi-echelon humanitarian response network, where the pre-disaster decisions of warehouse location and item pre-positioning are subject to uncertainties in relief item demand and vulnerability of roads and facilities following the disaster. Once the disaster strikes, relief transportation is accompanied by simultaneous repair of blocked roads, which delays the transportation process, but gradually increases the connectivity of the network at the same time. A two-stage stochastic program is formulated to model this system and a Sample Average Approximation (SAA) scheme is proposed for its heuristic solution. To enhance the efficiency of the SAA algorithm, we introduce a number of valid inequalities and bounds on the objective value. Computational experiments on a potential earthquake scenario in Istanbul, Turkey show that the SAA scheme is able to provide an accurate approximation of the objective function in reasonable time, and can help drive policy-based implications that may be applicable in preparation for similar potential disaster

Lateral transshipment of slow moving critical medical items

This research studies lateral transshipment of critical medical items that have low demands. Due to the high prices of medical items and their limited shelf lives, the expirations contribute significantly to the current prohibitively high cost of the healthcare system. Lateral transshipment between hospitals in a medical system provides opportunities to reduce the expiration costs. This paper studies the decision rule for lateral transshipment in a two-hospital system and extends the rule for the multiple-hospital cases. The decision rule takes the myopic best action by assuming no transshipments will be performed in the future. Numerical experiments demonstrate significant cost savings and the decision rule has a small gap from the upper bound of the total saving. The savings are more considerable when the difference of demand rates at different locations is large and the life time of the medical item is not too long or too short