A Fuzzy AHP-TOPSIS Approach to Supply Partner Selection in Continuous Aid Humanitarian Supply Chains

The selection of suitable supply partners is a strategic issue for managers working in humanitarian operations and has received little attention in the literature. In humanitarian operations, complexity characterizes the continuous-aid procurement operations, and the selection criteria can differ from those used in commercial supply chain settings. This paper advances knowledge by introducing a supply partner selection framework for continuous-aid procurement. A proposed multi-criteria decision-making model uses selection criteria attributes verified by the extant literature and by field experts. A fuzzy Analytic Hierarchy Process is then used to compute criterion weights, and a fuzzy Technique for Order Performance by Similarity to Ideal Solution is used to rank supply partner alternatives. Even with elevated levels of subjectivity, these techniques enable humanitarian operation stakeholders to select the best supply partner effectively. An actual case illustrates how the proposed framework efficiently identifies the most suitable continuous-aid supply partner for the prevailing situation

The pre-positioning of humanitarian aid: the warehouse location problem

The overarching objective of this thesis is to explore the warehouse location decision problem by considering regional and specific site attributes in the unique context of humanitarian relief organisation. This is to fill the gaps the revealed in the current understanding of location decision problem, particularly the lack of studies attempting to investigate humanitarian pre-positioned location decision problem with qualitative attributes opposed to the many previous studies focused on computerised optimisation model absence of the human judgements. Specifically, this research develops into case studies of the international humanitarian organisations selecting the warehouse attributes and locating the alternative warehouse locations. International humanitarian relief organisation aiding the refugees participated in the case study of the regional location selection problem for pre-positioned warehouse with five major attributes and 25 sub-attributes. Six international humanitarian relief organisations based in Dubai, UAE participated for specific warehouse location selection problem with five major attributes and 30 sub-attributes. The overall research design adopted in this thesis is as follows. First, the coherent humanitarian warehouse location decision attributes were developed in the basis of a literature and semi-structured interviews with practitioners whose organisation practice pre-positioned warehouse operation system. Secondly, two case studies were conducted for constructing the hierarchy structure for warehouse evaluation for regional and specific site location. In the first case study, 11 managerial level officers participated to construct the regional warehouse location decision attributes and evaluated the warehouse location for the organisation. In the second case study, panel members were form by 11 decision-makers from six different organisations constructed the hierarchical structure of the specific site warehouse location attributes for the evaluation. Thirdly, Analytic Hierarchy Process (AHP) is executed to acquire criteria weights and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to obtain the final ranking of the warehouse locations. Fuzzy set theory is adopted in the evaluation to deal with the fuzziness of decision-makers‟ preferences in decision making. In conclusion, this thesis extends the body of knowledge in pre-positioned warehouse location problem in the humanitarian relief logistics context by suggesting a MADM location method, AHP and TOPSIS, integrated with fuzzy set theory to understand the priority preference of regional (macro) and specific site (micro) warehouse location attributes and the selection of the optimal warehouse

Risk Analysis of Emergency Supply Chains

Unknowns and uncertainties are integral to any disaster relief operation. Activities of the emergency supply chain are usually performed in highly volatile environments and are prone to risks. Due to the complexity of the operating relief environment, relief organizations can only anticipate some supply chain disruptions. As such, they must take a comprehensive and proactive approach to uncertainties to manage multiple unexpected events. Therefore, this research aims to develop a comprehensive framework for risk management in emergency supply chains. This study adopts a comprehensive and rigorous procedure to explore the risk factors and mitigation strategies for emergency supply chains. The research design is divided into three phases; first, the risk factors and mitigation strategies are collected through an extensive literature review; next, the risk factors and risk mitigation strategies are verified with experts through high-level surveys and semi-structured interviews. Finally, based on the weight of risk factors estimated using the fuzzy analytic hierarchy process, risk factors mitigation strategies to overcome the risk factors are prioritized using the fuzzy technique for order performance by similarity to ideal solution that considers uncertainty and impreciseness rather than a crisp value. This study found and verified 28 emergency supply chain risk factors, which are categorised into two main categories: internal and external risks; four sub-categories: demand, supply, infrastructural, and environmental risks; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social, and political risks. War and terrorism, the impact of follow-up disasters, poor relief supplies, and sanctions and constraints that hinder stakeholder cooperation and coordination are the most significant risks. Finally, eight risk factor mitigation strategies; strategic stock, prepositioning of resources, collaboration and coordination, flexible transportation, flexible supply bases, logistics outsourcing, flexible supply contracts, and risk awareness/knowledge management were proposed and prioritised to overcome the risk factors so decision-makers can focus on these mitigation strategies. This study provides a more efficient, effective, robust, and systematic way to overcome risk factors and improve the effectiveness of emergency supply chains in disaster relief operations. This study is the first to objectively identify, categorise, and analyse emergency supply chains’ risk nature and frequency. Practitioners and policymakers can use the research findings to spot significant risk factors and appropriate mitigation strategies to reduce their effects. The risk profile will be a new database of risk factors affecting the emergency supply chain and allow stakeholders to immediately identify the disrupted emergency supply chain component

PREdictive model for DISaster response configuration (PREDIS decision platform)

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe extraordinary conditions of a disaster, require the mobilisation of all available resources, inducing the rush of humanitarian partners into the affected area. This phenomenon called the proliferation of actors, causes serious problems during the disaster response phase including the oversupply, duplicated efforts, lack of planning. The aim of this research is to provide a solution to reduce the partner proliferation problem. To that end the main research question is put forward as “How to reduce the proliferation of partners in a disaster response”? Panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2013 via regression analysis, MA and AHP gives rise to the formation of a predictive decision-making platform called PREDIS. It is capable of predicting the human impact of the disaster (fatality, injured, homeless) of up to 3% of errors and enables the decision makers to estimate the required needs for each disaster and prioritises them based on the disaster type and socio-economics of the affected country. It further renders it possible to rank and optimise the desired partners based on the decision maker’s preferences. Verification of the PREDIS through a simulation game design using a sample group of decision makers, show that this technique enables the user to decide within one hour after the disaster strike using the widely available data at the time of the disaster. It also enables non-experts to decide almost identically to experts in terms of the similarity of the choices and the speed of the decision.The lack of an extensive database for the potential humanitarian partners from which to choose, is the limitation of this research in addition to the lack of standardised set of minimum requirements for the suitable partners.The model is also as strong as its data feed which is inconsistent in various humanitarian sources

Models and Algorithms for the Optimisation of Replenishment, Production and Distribution Plans in Industrial Enterprises

Tesis por compendio[ES] La optimización en las empresas manufactureras es especialmente importante, debido a las grandes inversiones que realizan, ya que a veces estas inversiones no obtienen el rendimiento esperado porque los márgenes de beneficio de los productos son muy ajustados. Por ello, las empresas tratan de maximizar el uso de los recursos productivos y financieros minimizando el tiempo perdido y, al mismo tiempo, mejorando los flujos de los procesos y satisfaciendo las necesidades del mercado. El proceso de planificación es una actividad crítica para las empresas. Esta tarea implica grandes retos debido a los cambios del mercado, las alteraciones en los procesos de producción dentro de la empresa y en la cadena de suministro, y los cambios en la legislación, entre otros. La planificación del aprovisionamiento, la producción y la distribución desempeña un papel fundamental en el rendimiento de las empresas manufactureras, ya que una planificación ineficaz de los proveedores, los procesos de producción y los sistemas de distribución contribuye a aumentar los costes de los productos, a alargar los plazos de entrega y a reducir los beneficios. La planificación eficaz es un proceso complejo que abarca una amplia gama de actividades para garantizar que los equipos, los materiales y los recursos humanos estén disponibles en el momento y el lugar adecuados. Motivados por la complejidad de la planificación en las empresas manufactureras, esta tesis estudia y desarrolla herramientas cuantitativas para ayudar a los planificadores en los procesos de la planificación del aprovisionamiento, producción y distribución. Desde esta perspectiva, se proponen modelos realistas y métodos eficientes para apoyar la toma de decisiones en las empresas industriales, principalmente en las pequeñas y medianas empresas (PYMES). Las aportaciones de esta tesis suponen un avance científico basado en una exhaustiva revisión bibliográfica sobre la planificación del aprovisionamiento, la producción y la distribución que ayuda a comprender los principales modelos y algoritmos utilizados para resolver estos planes, y pone en relieve las tendencias y las futuras direcciones de investigación. También proporciona un marco holístico para caracterizar los modelos y algoritmos centrándose en la planificación de la producción, la programación y la secuenciación. Esta tesis también propone una herramienta de apoyo a la decisión para seleccionar un algoritmo o método de solución para resolver problemas concretos de la planificación del aprovisionamiento, producción y distribución en función de su complejidad, lo que permite a los planificadores no duplicar esfuerzos de modelización o programación de técnicas de solución. Por último, se desarrollan nuevos modelos matemáticos y enfoques de solución de última generación, como los algoritmos matheurísticos, que combinan la programación matemática y las técnicas metaheurísticas. Los nuevos modelos y algoritmos comprenden mejoras en términos de rendimiento computacional, e incluyen características realistas de los problemas del mundo real a los que se enfrentan las empresas de fabricación. Los modelos matemáticos han sido validados con un caso de una importante empresa del sector de la automoción en España, lo que ha permitido evaluar la relevancia práctica de estos novedosos modelos utilizando instancias de gran tamaño, similares a las existentes en la empresa objeto de estudio. Además, los algoritmos matheurísticos han sido probados utilizando herramientas libres y de código abierto. Esto también contribuye a la práctica de la investigación operativa, y proporciona una visión de cómo desplegar estos métodos de solución y el tiempo de cálculo y rendimiento de la brecha que se puede obtener mediante el uso de software libre o de código abierto.[CA] L'optimització a les empreses manufactureres és especialment important, a causa de les grans inversions que realitzen, ja que de vegades aquestes inversions no obtenen el rendiment esperat perquè els marges de benefici dels productes són molt ajustats. Per això, les empreses intenten maximitzar l'ús dels recursos productius i financers minimitzant el temps perdut i, alhora, millorant els fluxos dels processos i satisfent les necessitats del mercat. El procés de planificació és una activitat crítica per a les empreses. Aquesta tasca implica grans reptes a causa dels canvis del mercat, les alteracions en els processos de producció dins de l'empresa i la cadena de subministrament, i els canvis en la legislació, entre altres. La planificació de l'aprovisionament, la producció i la distribució té un paper fonamental en el rendiment de les empreses manufactureres, ja que una planificació ineficaç dels proveïdors, els processos de producció i els sistemes de distribució contribueix a augmentar els costos dels productes, allargar els terminis de lliurament i reduir els beneficis. La planificació eficaç és un procés complex que abasta una àmplia gamma d'activitats per garantir que els equips, els materials i els recursos humans estiguen disponibles al moment i al lloc adequats. Motivats per la complexitat de la planificació a les empreses manufactureres, aquesta tesi estudia i desenvolupa eines quantitatives per ajudar als planificadors en els processos de la planificació de l'aprovisionament, producció i distribució. Des d'aquesta perspectiva, es proposen models realistes i mètodes eficients per donar suport a la presa de decisions a les empreses industrials, principalment a les petites i mitjanes empreses (PIMES). Les aportacions d'aquesta tesi suposen un avenç científic basat en una exhaustiva revisió bibliogràfica sobre la planificació de l'aprovisionament, la producció i la distribució que ajuda a comprendre els principals models i algorismes utilitzats per resoldre aquests plans, i posa de relleu les tendències i les futures direccions de recerca. També proporciona un marc holístic per caracteritzar els models i algorismes centrant-se en la planificació de la producció, la programació i la seqüenciació. Aquesta tesi també proposa una eina de suport a la decisió per seleccionar un algorisme o mètode de solució per resoldre problemes concrets de la planificació de l'aprovisionament, producció i distribució en funció de la seua complexitat, cosa que permet als planificadors no duplicar esforços de modelització o programació de tècniques de solució. Finalment, es desenvolupen nous models matemàtics i enfocaments de solució d'última generació, com ara els algoritmes matheurístics, que combinen la programació matemàtica i les tècniques metaheurístiques. Els nous models i algoritmes comprenen millores en termes de rendiment computacional, i inclouen característiques realistes dels problemes del món real a què s'enfronten les empreses de fabricació. Els models matemàtics han estat validats amb un cas d'una important empresa del sector de l'automoció a Espanya, cosa que ha permés avaluar la rellevància pràctica d'aquests nous models utilitzant instàncies grans, similars a les existents a l'empresa objecte d'estudi. A més, els algorismes matheurístics han estat provats utilitzant eines lliures i de codi obert. Això també contribueix a la pràctica de la investigació operativa, i proporciona una visió de com desplegar aquests mètodes de solució i el temps de càlcul i rendiment de la bretxa que es pot obtindre mitjançant l'ús de programari lliure o de codi obert.[EN] Optimisation in manufacturing companies is especially important, due to the large investments they make, as sometimes these investments do not obtain the expected return because the profit margins of products are very tight. Therefore, companies seek to maximise the use of productive and financial resources by minimising lost time and, at the same time, improving process flows while meeting market needs. The planning process is a critical activity for companies. This task involves great challenges due to market changes, alterations in production processes within the company and in the supply chain, and changes in legislation, among others. Planning of replenishment, production and distribution plays a critical role in the performance of manufacturing companies because ineffective planning of suppliers, production processes and distribution systems contributes to higher product costs, longer lead times and less profits. Effective planning is a complex process that encompasses a wide range of activities to ensure that equipment, materials and human resources are available in the right time and the right place. Motivated by the complexity of planning in manufacturing companies, this thesis studies and develops quantitative tools to help planners in the replenishment, production and delivery planning processes. From this perspective, realistic models and efficient methods are proposed to support decision making in industrial companies, mainly in small- and medium-sized enterprises (SMEs). The contributions of this thesis represent a scientific breakthrough based on a comprehensive literature review about replenishment, production and distribution planning that helps to understand the main models and algorithms used to solve these plans, and highlights trends and future research directions. It also provides a holistic framework to characterise models and algorithms by focusing on production planning, scheduling and sequencing. This thesis also proposes a decision support tool for selecting an algorithm or solution method to solve concrete replenishment, production and distribution planning problems according to their complexity, which allows planners to not duplicate efforts modelling or programming solution techniques. Finally, new state-of-the-art mathematical models and solution approaches are developed, such as matheuristic algorithms, which combine mathematical programming and metaheuristic techniques. The new models and algorithms comprise improvements in computational performance terms, and include realistic features of real-world problems faced by manufacturing companies. The mathematical models have been validated with a case of an important company in the automotive sector in Spain, which allowed to evaluate the practical relevance of these novel models using large instances, similarly to those existing in the company under study. In addition, the matheuristic algorithms have been tested using free and open-source tools. This also helps to contribute to the practice of operations research, and provides insight into how to deploy these solution methods and the computational time and gap performance that can be obtained by using free or open-source software.This work would not have been possible without the following funding sources: Conselleria de Educación, Investigación, Cultura y Deporte, Generalitat Valenciana for hiring predoctoral research staff with Grant (ACIF/2018/170) and the European Social Fund with the Grant Operational Programme of FSE 2014-2020. Conselleria de Educación, Investigación, Cultura y Deporte, Generalitat Valenciana for predoctoral contract students to stay in research centers outside the research centers outside the Valencian Community (BEFPI/2021/040) and the European Social Fund.Guzmán Ortiz, BE. (2022). Models and Algorithms for the Optimisation of Replenishment, Production and Distribution Plans in Industrial Enterprises [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/187461Compendi

Optimization for Decision Making II

In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner

A hybrid approach to achieve organizational agility: An empirical study of a food company

Purpose: In today’s intense global competition, agility is advocated as a fundamental characteristic for business survival and competitiveness. The purpose of this paper is to propose a practical methodology to achieve and enhance organizational agility based on strategic objectives. Design/methodology/approach: In the first step, a set of key performance indicators (KPIs) of the organization being studied are recognized and classified under the perspectives of balanced scorecard (BSC). Critical success factors are then identified by ranking the KPIs according to their importance in achieving organizational strategic objectives using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In the second step, three houses of quality (HOQs) are constructed sequentially to identify and rank the main agile attributes, agile enablers, and improvement paths. In addition, in order to translate linguistics judgments of practitioners into numerical values in building HOQs, fuzzy logic is employed. Findings: The capability of the proposed methodology is demonstrated by applying it to a case of a multi-national food company in Iran. Through the application, the company could find the most suitable improvement paths to improve its organizational agility. Research limitations/implications: A limited number of KPIs were chosen due to computational and visual constraints related to HOQs. Another limitation, similar to other agility studies, which facilitate decision making among agility metrics, was that the metrics were more industry-specific and less inclusive. Practical implications: A strong practical advantage for the application of the methodology over directly choosing agility metrics without linking them is that through the methodology, the right metrics were selected that match organization’s core values and marketing objectives. While metrics may ostensibly seem unrelated or inappropriate, they actually contributed to the right areas where there were gaps between the current and desired level of agility. It would otherwise be impossible to choose the right metrics without a structured methodology. Originality/value: This paper proposes a novel methodology for achieving organizational agility. By utilizing and linking several tools such as BSC, fuzzy TOPSIS, and quality function deployment (QFD), the proposed approach enables organizations to identify the most appropriate agile attributes, agile enablers, and subsequently agile improvement paths