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In this paper, we develop a decisional framework and a mathematical model for the sustainable design of biodiesel supply chain networks (BSCND). We consider a broad group of sustainable aims, i.e. standard economic goals (revenue and logistics costs of BSCND), environmental issues based on a biodiesel production life cycle assessment (LCA), and the social incidental aspects (e.g. crime control, political stability, and community attitude, among others). The framework begins with a simulation of the biodiesel production system, feeding later, with suitable input parameters and suitable solutions, and a macrolocation model designed to establish the regional positioning of biofuel conversion plants. Optimal regions are used as initial feasible solution space for the proposed micro-location model. In this part of the framework, we introduce an adaptation of Extended Goal Programming to rank the best municipalities (definitive locations) emphasizing the social aspects under consideration. The framework application is set up in the following Colombian context: first generation biodiesel production from palm oil feedstock. Our computational results indicate that the Colombian city of Rionegro (in the Santader region) is the most sustainable location for a new biodiesel plant.
5/9/2017 A decisional simulation-optimization framework for sustainable facility location of a biodiesel plant in Colombia 1/3
Article outline Show full outline
1. Introduction
2. Facility location within the frame of B
3. Proposed simulation-optimization fra
4. A realistic case study of BSCND
5. Conclusions
Appendix A. Biodiesel production flows
Appendix B. Input data for simulation pr
Uncited reference
Figures and tables
Table 1
Table 2
Table 3
YaselCostaa,b, ,AlexandraDuartec, ,WilliamSarached, ,
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... Mixed integer linear programming [26,29,34,85,40,41,55,58,59,84 Table 9 Sim-opt references according to the solving approach. ...
... Exact method Heuristic Metaheuristic [26] X [28] TS [29] X [30] GA, EP [32] X [34] ILS [85] X [107] X [37] GA [40] X [41] X [55] X [58] X [59] X [79] GA [84] X [86] OptQuest [88] X [90] GA [92] NSGA-II [93] X [95] X [106] X [135] X [136] X [137] PSO [151] GA [154] X [158] GA [162] OAA [163] NP, OCBA [166] X Tabu search Genetic Algorithm Evolutionary Programming Iterated local search Non-dominated Sorting Genetic Algorithm II Particle swarm optimization Outer-approximation algorithm Nested Partitioning Optimal Computing Budget Allocation model to design a Colombian supply chain for bio-diesel production and distribution from palm oil feed-stock. Firstly, a deterministic simulation model is used to design the production process and obtain the production cost. ...
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This paper presents a multi-objective possibilistic programming model to design a second-generation biodiesel supply chain network under risk. The proposed model minimizes the total costs of biodiesel supply chain from feedstock supply centers to customer centers besides minimizing the environmental impact (EI) of all involved processes under a well-to-wheel perspective. Non-edible feedstocks are considered for biodiesel production. Variable cultivation cost of non-edible feedstock is assumed to be non-linear and dependent upon the amount of cultivated area. New formulation of possibilistic programming method is developed which is able to minimize the total mean and risk values of problems with possibilistic-based uncertainty. To solve the proposed multi-objective model, a hybrid solution approach based on flexible lexicographic and augmented ɛ-constraint methods is proposed which is capable to find appropriate efficient solutions from the Pareto-optimal set. The performance of the proposed possibilistic programming method as well as the developed solution approach are evaluated and validated through conducting a real case study in Iran. The outcome of this study demonstrates that high investment cost is required for improving the environmental impact and risk of sustainable biodiesel supply chain network design under risk. Decision maker preferences are required for suitable trade-off among total costs, risk values and environmental impact.
This paper addresses the optimal design and location facility of biodiesel supply chains (BSC) under economic and environmental criteria. The economical aspect scale is assessed by the total annualized cost. The environmental objective is evaluated by the total GHG (Green House Gases) emissions for a whole life cycle. A mathematical model that can be used to design the supply chain (SC) and manage the logistics of a biodiesel is proposed. The model determines the number, size and location of biorefineries needed to produce biodiesel using the available biomass. Mixed-integer linear programming model is proposed that takes into account infrastructure compatibility, demand distribution, as male as the size and location of biorefineries needed to produce biodiesel using the available biomass and carbon tax. An important feature of the model proposed is the account requirement of crop rotation important from agronomic perspective. In second part of this study Bulgaria is examined as the testing ground of the model. © 2014 Bulgarian Academy of Sciences, Union of Chemists in Bulgaria.
This chapter presents the principles of biorefining. The biorefinery concept embraces a wide range of technologies able to separate biomass resources (wood, grasses, corn, etc.) into their building blocks, (carbohydrates, proteins, fats, etc.) which can be converted to value-added products, biofuels, and chemicals. A biorefinery is a facility (or network of facilities) that integrates biomass conversion processes and equipment to produce transportation biofuels, power, and chemicals from biomass. The biorefinery concept is analogous to today's petroleum refinery, which produces multiple fuels and products from petroleum. The elemental and chemical structure of biorefinery raw materials differs from that on which the current fossil refinery and chemical industry is based. Chemical and elemental composition of petroleum is compared with some lignocellulosic biomass feedstocks in feedstock is that, unlike biomass, it is very low in oxygen content. Biomass is constituted of an enormous variety of plant species with varying morphology and chemical composition. However, regardless of the phenotype, five main biomass components can be identified worldwide: lipids, starch, cellulose, hemicelluloses, lignin, and proteins. It clearly appears that lignocellulosic biomass components such as cellulose, hemicelluloses, and lignin are by far the most abundant. Since they can be even gathered from waste streams (e.g., crop residues, paper and wood industries), or directly harvested from forests or biomass stands through sustainable management, their price tend to be lower than other biomass sources which need a dedicated agricultural plot.
This paper presents a life cycle assessment (LCA) based multi-period and multi-objective biofuel supply chain model. The objective functions are total discounted profit, average fossil energy input per MJ biofuel and average greenhouse gases emission per MJ biofuel (economic, energy, environmental, 3E). Considering seasonal factor and storage problem, a multi-period model was required. Furthermore, to investigate the expansion of the supply chain, the time span of the model was set to be 3 years. The locations of biomass feedstock, biofuel factories and markets were considered as decision variables in the model. The non-linear objective functions were transformed into linear constraints by using the ε-constraint method. After that, the model was solved as a MILP problem. A surface of the Pareto optimal solutions was obtained by linearly interpolating the non-inferior solutions. The surface revealed the tradeoff among 3E objectives. In the case study, this model was used to design an experimental biofuel supply chain for China.