Integrated strategic and tactical optimization of animal-waste sourced biopower supply chains

International audience—Many models have been recently developed for the optimization of biomass related supply chains. However, models for biopower supply chains powered by animal waste have not received much attention yet. In this paper, we propose a mixed integer linear programming model for supplier selection and procurement planning for a biopower plant. The model integrates time window constraints for the collection of animal waste as well as inventory constraints. We show that the model is intractable with a state-of-the art commercial solver and propose a heuristic approach based on the Adaptive Large Neighbourhood Search (ALNS) framework. We show the efficiency of this approach on a case study in central France

Contribution to the development of efficient algorithms for solving complex single-objective and multi-objective optimization models

L’optimització en enginyeria de processos és un àrea molt estesa que ha anat evolucionant al llarg del temps i ha passat de ser una metodologia d'interès purament acadèmic a una tecnologia que té, i que contínua tenint, gran impacte en la indústria. En aquesta tesi ens hem centrat en el desenvolupament mètodes basats en dues eines típiques d'optimització: programació matemàtica i metaheurístiques. Els objectius d'aquesta tesi són: el primer és desenvolupar una metaheuristica híbrida per a l'optimització del disseny de cadenes de subministrament, d'un sol objectiu (cost o benefici), on tots els paràmetres són coneguts a priori; el segon és desenvolupar un algorisme efectiu per a reducció d'objectius facilitant la resolució de problemes multi-objectiu; i finalment s'han implementat una sèrie de millores en el mètode de la restricció èpsilon per millorar l'eficiència en la resolució de problemes multi-objectiu. Tots els algorismes presentats han estat comparats i avaluats amb els mètodes establerts per la literatura.La optimización en ingeniería de procesos es un área muy extensa que ha ido evolucionando a lo largo del tiempo y ha pasado de ser una metodología de interés puramente académico a una tecnología que tiene, y que continua teniendo, gran impacto en la industria. En esta tesis nos hemos centrado en el desarrollo de métodos basados en dos herramientas típicas de optimización: programación matemática y metaheurísticas. Los objetivos de esta tesis son: el primero es desarrollar una metaheuristica híbrida para la optimización del diseño de cadenas de suministro, de un solo objetivo (coste o beneficio), donde todos los parámetros son conocidos a priori; el segundo es desarrollar un algoritmo efectivo para la reducción de objetivos facilitando la resolución de problemas multi-objetivo; y finalmente se han implementado una serie de mejoras en el método de la restricción epsilon para mejorar la eficiencia en la resolución de problemas multi-objetivo. Todos los algoritmos presentados han sido comparados y evaluados con los métodos establecidos por la literatura.Optimization has become a major area in process systems engineering. It has evolved from a methodology of academic interest into a technology that has and continues to make significant impact in industry. In this thesis we have focused on development of tools based on two standard optimization methods: mathematical programming and metaheuristics. The objectives of this thesis are: firstly, the development of a hybrid metaheuristic for optimizing the design of supply chains, single objective (cost or benefit), where all parameters are known previously; secondly, the development of an effective algorithm for objective reduction facilitating the resolution of multi-objective problems; and finally, we improved the epsilon-constraint algorithm in multi-objective optimization. All the algorithms presented have been assessed with the methods established in the literature

Computer-based tools for supporting forest management. The experience and the expertise world-wide

Report of Cost Action FP 0804 Forest Management Decision Support Systems (FORSYS)Computer-based tools for supporting forest management. The experience and the expertise world-wide answers a call from both the research and the professional communities for a synthesis of current knowledge about the use of computerized tools in forest management planning. According to the aims of the Forest Management Decision Support Systems (FORSYS) (http://fp0804.emu.ee/) this synthesis is a critical success factor to develop a comprehensive quality reference for forest management decision support systems. The emphasis of the book is on identifying and assessing the support provided by computerized tools to enhance forest management planning in real-world contexts. The book thus identifies the management planning problems that prevail world-wide to discuss the architecture and the components of the tools used to address them. Of importance is the report of architecture approaches, models and methods, knowledge management and participatory planning techniques used to address specific management planning problems. We think that this synthesis may provide effective support to research and outreach activities that focus on the development of forest management decision support systems. It may contribute further to support forest managers when defining the requirements for a tool that best meets their needs. The first chapter of the book provides an introduction to the use of decision support systems in the forest sector and lays out the FORSYS framework for reporting the experience and expertise acquired in each country. Emphasis is on the FORSYS ontology to facilitate the sharing of experiences needed to characterize and evaluate the use of computerized tools when addressing forest management planning problems. The twenty six country reports share a structure designed to underline a problem-centric focus. Specifically, they all start with the identification of the management planning problems that are prevalent in the country and they move on to the characterization and assessment of the computerized tools used to address them. The reports were led by researchers with background and expertise in areas that range from ecological modeling to forest modeling, management planning and information and communication technology development. They benefited from the input provided by forest practitioners and by organizations that are responsible for developing and implementing forest management plans. A conclusions chapter highlights the success of bringing together such a wide range of disciplines and perspectives. This book benefited from voluntary contributions by 94 authors and from the involvement of several forest stakeholders from twenty six countries in Europe, North and South America, Africa and Asia over a three-year period. We, the chair of FORSYS and the editorial committee of the publication, acknowledge and thank for the valuable contributions from all authors, editors, stakeholders and FORSYS actors involved in this project

Biorenewable value chain optimisation with multi-layered value chains and advanced analytics

A crucial element of the quest of curbing carbon dioxide emissions is deemed to rely on a biobased economy, which will rely on the development of economically and environmentally sustainable biorefining systems enabling a full exploitation of lignocellulosic biomass (and its macrocomponents such as cellulose, hemicellulose, and lignin) for the co-production of biofuels and bioderived platform chemicals. The thesis aims to develop comprehensive modelling frameworks to provide, through optimisation techniques, holistic decision-making regarding the strategic design and systematic planning of advanced biorefining supply chain networks. Therefore, the modelling of the entire value chain behaviour, involving both upstream and downstream aspects within a temporal and geographical context, is of great importance in this study. A deterministic, spatially explicit, multi-echelon and multi-period Mixed Integer Linear Programming prototype modelling framework is developed for the identification of profitably optimal strategic and operating decisions regarding a full supply chain system, integrated with a technology superstructure of multiple biomass feedstocks, bioproducts and processing portfolios. The potential dimensionality reduction of the resulting large-scale optimisation problem is explored by utilising a bilevel decomposition algorithm. The financial sustainability of such biobased supply chains is further analysed through two-stage stochastic optimisation and risk management models, incorporating biomass cultivation yield uncertainties and expected downside risk, respectively. Finally, greenhouse gas emission factors are added to the prototype modelling approach through a multi-objective optimisation scheme to steer decision-making on biorefining supply chain systems under both economic and environmental criteria, comparing two different solution procedures. The developed models are applied to a Hungarian case study of lignocellulosic biorefining production systems. An additional case study in a Southeastern Romanian region and Marseille, regarding a first-generation biorefining supply chain for the production of castor oil, is undertaken to further examine the compatibility and efficiency of the generic deterministic model.Open Acces

A Large Neighborhood Search heuristic for Supply Chain Network Design

24 pagesMany exact or approximate solution techniques have been used to solve facility location problems and more generally supply chain network design problems. Yet, the Large Neighborhood Search technique (LNS) has almost never been proposed for solving such problems, although it has proven its efficiency and flexibility in solving other complex combinatorial optimization problems. In this paper we propose an LNS framework for solving a four-layer single period multi-product supply chain network design problem involving multimodal transport. Location decisions for intermediate facilities (e.g. plants and distribution centers) are made using the LNS while transportation modes and product flow decisions are determined by a greedy heuristic. As a post-optimization step, we also use linear programming to determine the optimal product flows once the logistics network is fixed. Extensive experiments based on generated instances of different sizes and characteristics show the effectiveness of the method compared with a state-of-the-art solver

Renewable hydrogen supply chains: A planning matrix and an agenda for future research

Worldwide, energy systems are experiencing a transition to more sustainable systems. According to the Hydrogen Roadmap Europe (FCH EU, 2019), hydrogen will play an important role in future energy systems due to its ability to support sustainability goals and will account for approximately 13% of the total energy mix in the coming future. Correct hydrogen supply chain (HSC) planning is therefore vital to enable a sustainable transition, in particular when hydrogen is produced by water electrolysis using electricity from renewable sources (renewable hydrogen). However, due to the operational characteristics of the renewable HSC, its planning is complicated. Renewable hydrogen supply can be diverse: Hydrogen can be produced de-centrally with renewables, such as wind and solar energy, or centrally by using electricity generated from a hydro power plant with a large volume. Similarly, demand for hydrogen can also be diverse, with many new applications, such as fuels for fuel cell electrical vehicles and electricity generation, feedstocks in industrial processes, and heating for buildings. The HSC consists of various stages (production, storage, distribution, and applications) in different forms, with strong interdependencies, which further increase HSC complexity. Finally, planning of an HSC depends on the status of hydrogen adoption and market development, and on how mature technologies are, and both factors are characterised by high uncertainties. Directly adapting the traditional approaches of supply chain (SC) planning for HSCs is insufficient. Therefore, in this study we develop a planning matrix with related planning tasks, leveraging a systematic literature review to cope with the characteristics of HSCs. We focus only on renewable hydrogen due to its relevance to the future low-carbon economy. Furthermore, we outline an agenda for future research, from the supply chain management perspective, in order to support renewable HSC development, considering the different phases of renewable HSCs adoption and market development