An Excel-Based Decision Support System for Supply Chain Design and Management of Biofuels

Abstract

This article presents a Decision Support System (DSS) to aid managers with supply chain (SC) design and logistics management of biomass-for-biofuel production. These tools play a very important role in efficiently managing biomass-for-biofuel SCs and have the potential to reduce the cost of biofuels. The proposed model coordinates the long-term decisions of designing a SC with the medium term decisions of logistics management. This system has the ability to (a) identify locations and capacities for biorefineries, given the availability of biomass and costs; (b) estimate the minimum cost of delivering biofuels, which include transportation, investment, and processing costs; and (c) perform sensitivity analyses with respect to a number of parameters. Visual Basic for Applications (VBA) is used to create the interface of the DSS, and Excel's CPLEX Add-In is used to solve the mathematical models.

GIS-based allocation of herbaceous biomass in biorefineries and depots

“…Locating a facility and determining the nameplate capacity of the facility is the most crucial decision to realize an efficient SCh due to the high investment costs and availability of feedstock [27,28]. The facility location problem (FLP) in general networks is known as a non-deterministic polynomial-time hard (NP-hard) problem to solve for optimality.…”

“…Many studies have approached the facility location problem, as well as the capacitated FLP (CFLP) through heuristics such as the local search algorithm, linear-programming rounding, dual-based ascent, lagrangian relaxation, greedy algorithms and greedy augmentation [31][32][33][34][35][36][37][38][39][40][41]. Acharya et al [27] presented a decision support system that could be used by managers to solve the SCh problems of capacity and location for a single new or multiple new biorefineries. They addressed four SCh problems: the transportation problem (when location and capacity is known), the capacity allocation and transportation problem (when location is known but the capacity is unknown), the facility location problem (when capacity is known and location is unknown), and the capacitated facility location problem (when capacity and location is unknown).…”

“…Panichelli & Gnansounou applied a least-cost approach to locate various bioenergy facilities (of a fixed capacity) simultaneously based on the significant variability of farmgate prices [48]. Most of the literature assumes that available feedstock for a county is in the centroid [27,49,50] or in county seats [15].…”

Optimization Models for the Continuous Review Inventory System

“…This literature review first addresses prior work in establishing a probability distribution for lead time demand, then reviews the modeling techniques that are most closely related to the approach described in this paper. Bartolacci, LeBlanc, Kayikci, & Grossman (2012) give an excellent overview of optimization models suggested for many different logistics applications, and Acharya, Gonzales, Eksioglu, & Arora (2014) describe an Excel implementation of a decision support tool in Excel for management of a supply chain.…”

A Novel Mixed Integer Programming Formulation for Selecting the Best Renewable Energies to Invest

“…Although fossil fuel availability is decreasing, its demand and price and environmental concerns are growing. So identifying a sustainable energy source seems necessary (Acharya et al, 2014). In other hand, the current pattern of energy generation, which is mainly focused on fossil fuels and centralized electricity, ignores energy requirements of the isolated areas such as rural area and islands.…”