Optimizing planning decisions in the fruit supply chain

La agro-indústria xilena ha experimentat un augment constant d'exportacions de fruita processada en la darrera dècada, arribant a un augment del 107% en volum total i 185% en valor. Aquest creixement significa que la cadena de subministrament de fruita fresca, ja sigui per a conserva, deshidratats, congelat i fresc de fruites o sucs, requereix suport per fer gestió cada vegada més eficient. Fins ara, alguns problemes relacionades directament amb la necessitat de millorar la competitivitat del sector no han estat encara tractats. En els últims anys els costos de producció han augmentat degut principalment a l'escassetat de mà d'obra i la mala qualitat de la fruita fresca. Això fa que millorar l'eficiència de cadena de subministrament i per tant la competitivitat agroindústria, requereixi de noves eines que serveixin de suport a la presa de decisions a la cadena de subministrament de fruita fresca. En aquest context, l'objectiu general d'aquesta recerca era desenvolupar un conjunt d'eines per donar suport a les decisions tàctiques de la cadena de subministrament de la fruita i millorar la gestió de compres, de les cambres frigorífiques i el transport. Tres importants contribucions es fan en aquest treball de recerca. La primera d'elles té a veure amb l'estat de l'art de les cadenes de subministrament, revisant els models d'optimització aplicats a les cadenes de subministrament de fruita fresca. La segona consisteix a proporcionar quatre eines per recolzar les decisions tàctiques de les cadenes de subministrament de fruita fresca, en concret, tres models matemàtics per a l'optimització de les decisions que donen suport a la selecció de productors i la compra de fruita fresca, el seu posterior emmagatzematge i transport i la proposta d'un model per a la gestió de cambres frigorífiques. Una tercera aportació és la proposta d'un sistema de suport a la presa de decisió (DSS), permeti la transparència del coneixement dels models anteriors al sector per al seu us pràctic. Destacar el valor addicional del treball a l'haver aplicat els models a casos reals. Així, tots el models proposats van ser validats amb l'ajut de l'agroindústria de la regió centre-sud de Xile que tenien problemes amb la seva cadena de subministrament.The Chilean agro-industry has experienced a steady increase of industrialized fruit exports over the last decade, reaching a total volume increase of 107% and 185% in value. This growth means that the fresh fruit supply chain, either for preserved, frozen, dehydrated, fresh fruit or juices, requires support in order to make management increasingly more efficient. So far, some problems directly related to the need to improve the sector´s competitiveness have not yet been addressed. In the last few years production costs have risen mainly due to labor shortage and poor quality of raw material (fresh fruit). That is why, improving the supply chain efficiency and thus the agro-industry competitiveness, particularly in the center-south region of the country, requires new tools that could support decisions making regarding the fresh fruit supply chain. Within this context, the general objective of this research was to develop a set of tools aiming to support tactical decisions that could enhance management of fresh fruit purchasing, cold storage, transport, and opening of cold chambers. Three important contributions are made in this research study. The first one has to do with the state-ofthe- art of supply chains management, by reviewing optimization models applied to fresh fruit supply chains. The second one consists in providing four tools to support tactical decisions regarding fresh fruit supply chains, specifically, three mathematical models for the optimization of decisions that support the selection of growers and the purchasing of fresh fruit, their subsequent storage and transportation, and the proposal of a mathematical model for cold storage management. The third contribution is the proposal of a Decision Support System (DSS), which aids in decisions about growers selection and purchasing of fresh fruit, as well as its subsequent storage and transportation. Finally, there is an important additional contribution that involves the application of the models to real cases. All models proposed were created and validated with the support of agro-industries from the centersouth region of the country having problems with their supply chain, which were addressed in this research study

Advances in Data-Driven Modeling and Global Optimization of Constrained Grey-Box Computational Systems

The effort to mimic a chemical plant’s operations or to design and operate a completely new technology in silico is a highly studied research field under process systems engineering. As the rising computation power allows us to simulate and model systems in greater detail through careful consideration of the underlying phenomena, the increasing use of complex simulation software and generation of multi-scale models that spans over multiple length and time scales calls for computationally efficient solution strategies that can handle problems with different complexities and characteristics. This work presents theoretical and algorithmic advancements for a range of challenging classes of mathematical programming problems through introducing new data-driven hybrid modeling and optimization strategies. First, theoretical and algorithmic advances for bi-level programming, multi-objective optimization, problems containing stiff differential algebraic equations, and nonlinear programming problems are presented. Each advancement is accompanied with an application from the grand challenges faced in the engineering domain including, food-energy-water nexus considerations, energy systems design with economic and environmental considerations, thermal cracking of natural gas liquids, and oil production optimization. Second, key modeling challenges in environmental and biomedical systems are addressed through employing advanced data analysis techniques. Chemical contaminants created during environmental emergencies, such as hurricanes, pose environmental and health related risks for exposure. The goal of this work is to alleviate challenges associated with understanding contaminant characteristics, their redistribution, and their biological potential through the use of data analytics

The spatial distribution and interregional dynamics of vegetable production in Thailand

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Proceedings of the XIII Global Optimization Workshop: GOW'16

[Excerpt] Preface: Past Global Optimization Workshop shave been held in Sopron (1985 and 1990), Szeged (WGO, 1995), Florence (GO’99, 1999), Hanmer Springs (Let’s GO, 2001), Santorini (Frontiers in GO, 2003), San José (Go’05, 2005), Mykonos (AGO’07, 2007), Skukuza (SAGO’08, 2008), Toulouse (TOGO’10, 2010), Natal (NAGO’12, 2012) and Málaga (MAGO’14, 2014) with the aim of stimulating discussion between senior and junior researchers on the topic of Global Optimization. In 2016, the XIII Global Optimization Workshop (GOW’16) takes place in Braga and is organized by three researchers from the University of Minho. Two of them belong to the Systems Engineering and Operational Research Group from the Algoritmi Research Centre and the other to the Statistics, Applied Probability and Operational Research Group from the Centre of Mathematics. The event received more than 50 submissions from 15 countries from Europe, South America and North America. We want to express our gratitude to the invited speaker Panos Pardalos for accepting the invitation and sharing his expertise, helping us to meet the workshop objectives. GOW’16 would not have been possible without the valuable contribution from the authors and the International Scientific Committee members. We thank you all. This proceedings book intends to present an overview of the topics that will be addressed in the workshop with the goal of contributing to interesting and fruitful discussions between the authors and participants. After the event, high quality papers can be submitted to a special issue of the Journal of Global Optimization dedicated to the workshop. [...

A Biofuel Supply Chain Equilibrium Analysis with Subsidy Consideration

Growing environmental concerns in the last few decades along with the energy security issues have led governments to take actions to reduce their dependence on fossil fuels and enhance renewable energy usage, including biofuels. Enforcement of federal or state mandates and regulations that obligate a certain amount of biofuel production are one of the main levers that governments use to achieve their goals. In the U.S. as an example, Renewable Fuel Standard (RFS) requires the production of 36 billion gallons of ethanol by 2022, 21 billion gallons of which should be advanced biofuels derived from biostocks other than corn starch. In parallel with making regulations, governments also incentivize the biofuel producers and farmers who provide the input biomass by paying subsidies to promote the industry. In this research, one of our main goals is to study the government’s role as both a regulator and incentive payer in the biofuel production industry. In the first chapter we consider a pilot biofuel supply chain problem, in which a farmer supplies two downstream refineries with non-identical crops (corn and energy crop). The problem has been modeled as a multi-leader-single-follower game to derive the farmer’s decisions on land allocation as well as refineries’ proposed prices to the farmer for their raw materials. We consider subsidizing the farmer and the refinery that uses the energy crop to study whether a subsidy plan can enhance the advanced biofuel production and meet the existing mandate. We solve the problem under four cases based on the willingness of the farmer to sell corn to the food market as well as the availability of farming land expansion. The Nash Equilibrium (NE) is derived for all cases, and parametric analyses are used to study the effect of subsidies on the profit of the players and the total social welfare of the supply chain. We observe that a government’s expenditure can be offset by the increase of the social welfare under certain circumstances. We find the minimum budget requirement to meet the EPA’s mandate and show that a specific budget can be distributed to the farmer and the refineries in different ways while obtaining the same results. In Chapter 3, we extend the above equilibrium analysis by relaxing a simplifying assumption regarding the capacity of the refineries, which assumes that the refineries can process any amount of crop from the land that the farmer may allocate to them. Relaxing this assumption gives us the possibility of analyzing the problem under more general circumstances, although the assumption may be acceptable in a relatively small regional scope. We obtain closed form solutions for the supply chain equilibrium under the existence of the new capacity constraints and find that refineries offer lower prices under the new condition, while their profit is larger. However, this is not the case for the farmer, and her profit diminishes under this capacitated problem. In Chapter 4, we extend the scope of our problem by generalizing the model to consider multiple players and make conclusions more general. Our bilevel supply chain is modeled as an equilibrium problem with equilibrium constraints (EPEC) and solved using a linearization method and a commercial solver of GAMS. We perform several analyses including the effect of the farmer’s cost structure and the number of the refineries on a few socio-economic measures. We also perform a sensitivity analysis on a few critical industry and market parameters. Through our analyses, we first find that the budget requirement to meet the government’s goal is higher than what other similar works have estimated. Second, we find that as new refineries are built, the government should spend more on the subsidy to obtain the goal; however, the total social welfare increases because of an increase in the biofuel market consumer surplus from lower fuel price. We show that the government’s expenditure will not be offset by the increase of the social welfare in this multi-player case as the required conditions found from Chapter 2 do not hold. Finally, we find that the advanced biofuel technology improvement is the most important factor among the considered industry related factors in reducing the subsidy requirements. Finally, in Chapter 5, we summarize the introduced models in previous chapters, the effect of the capacity constraint, and the effect of the competition