Research brief: Network planning in supply chain management

Li Liang, email at

Supply chain network can be large and sophisticated, since it can involve many individual companies and many different processes and activities. Supply chain network planning is also very sophisticated, since it needs to cooperate those different individual companies and integrate many different processes and activities in the supply chain network in order to improve the value of products or minimize the system-wide costs but still satisfy the demand of customer with a good level (Che and Sha 2006). It is easy to say that the supply chain network planning can minimize cost and still maintain a good service level, but to actually achieve them both, it needs a lot of effort. Take a very straightforward example. It exists an obvious tradeoff between these two objectives, that is, if the supply chain needs to maintain a high service level, its system-wide cost will definitely increase, or if the supply chain needs to minimize its system-wide cost, the service level needs to give way. It seems that balancing the tradeoff is an art in supply chain network planning. Simchi-Levi et al (2008) stated that Supply chain network planning can help companies to:

  • Balance the cost trade off among inventory, transportation, and manufacturing.
  • Balance supply and demand under uncertainty through effective inventory management and positioning
  • Balance the available recourses to select the most appropriate product sourcing facilities.

Figure 1. Three steps of supply chain network planning

Associated with the above advantages, supply chain network planning can be divided in three steps as shown in Figure 1: planning, positioning and allocation. According to Simchi-Levi et al (2008), network design provides a physical configuration and infrastructure for supply chain. To achieve this objective, the data about locations of each facilities (suppliers, production plants, warehouses, distribution centers, retailers and even customers), all product information, annual demand, costs of each supply chain activities, and customer service requirements need to be collected first. After that, this huge amount of original data need to be aggregated to reduce the variance and for further utilization. The aggregated data would then be used to estimate transportation rates, mileage between two locations, warehouse costs, warehouse size, warehouse locations, service level, and future demand. The estimated data would be used to construct the supply chain network model, then both model and the estimated data would be validated by comparing the output of model with the existing data. After the validation, the model can be optimized by using mathematical optimization techniques or simulation model.

Inventory positioning is very difficult because it needs to determine the inventory control mechanism for each form of inventory (raw material inventory, work-in-process inventory, and finished product inventory), which needs to consider a lot of information. Such as production cost, distribution cost, inventory management cost, and even service level. There exist a lot of approaches for inventory management, such as (Q, R) policy, base-stock policy or critical fractile. The (Q, R) policy refers to calculate the optimal order quantity Q and reorder point R, and then place the order with a quantity of Q when inventory level reach the reorder point. The base-stock policy refers to calculate the base stock level and safety stock, when inventory level reach the safety stock level, it order up to the base stock level. The critical fractile refers to using the overage cost and underage cost to determine the optimal order quantity. Usually, the cumulative distribution function of the demand equals to the coverage cost divided by the sum of overage cost and underage cost.

Resource allocation can be done by using supply chain master planning. Master planning coordinates flows between each site and try to find the most effective way to meet demand forecast in a season cycle. It can maximize the profit or minimize the cost by balancing the demand forecasts with different capacities, and allocating production quantities to different sites to avoid bottlenecks (Stadtler 2005).

Planning the supply chain network is a very complex process but important, it involves in a set of strategic level decisions that would impact a supply chain’s future overall performance (Bahazadeh 2016). Planning of the supply network through these three steps can provide a company with a solid foundation, a better starting point, and further globally optimize supply chain performance


  • Babazadeh, R. (2016). Optimal design and planning of biodiesel supply chain considering non-edible feedstock. Renewable and Sustainable Energy Reviews, available online 15 November 2016
  • Simchi-Levi, D., Simchi-Levi, E., & Kaminsky, P. Shankar, R. (2008). Designing and managing the supply chain: Concepts, strategies, and case studies 3rd edition. New York: McGraw-Hill.
  • Sha, D.Y., Che, Z.H. (2006). Supply china network design: partner selection and production/distribution planning using a systematic model. Journal of the operational research society. 57 (1) 52-62
  • Stadtler, H. (2006). Supply chain management and advanced planning—basics, overview and challenges. European Journal of Operational Research. 163 (3) 575-588



Understanding Biofuel Classification

by Gaurav Kakkar,

The prospects of modernizing the use of biomass and developing cleaner liquid fuels to address concerns of energy cost, security and global warming associated with fossil fuels have led to a greater interest in Biofuels (United Nations, 2008). As classified by the UN (2008), the term biofuel means “any liquid fuel made from plant material that can be used as a substitute to petroleum-derived fuel”. International Energy Agency further adds gaseous fuels from biomass based sources to biofuels (IEA, Bioenergy, 2016). This broad term includes the familiar ones like ethanol made from sugar syrups or diesel like fuel made from plant oils to not so common ones like butanol, di-methyl ether (DME) or Fisher-Tropsch Liquids (FTL) made from lignocellulosic biomass. Moreover, as reported by IEA (2011), biofuels alone have the potential to cover up to 27% of the global transportation fuel requirements by 2050. Thus it is extremely important to understand uniform classification systems of biofuels that are globally adopted and the associated production technology. This article discuss two different classification types of biofuels based upon production technologies and biomass source.

Classification according to generations

 There are no strict technical definitions for this classification. The main distinction between them is the feedstock used and associated conversion method used. Following section discuss this classification in detail.

2. First generation: This category includes biofuels produced from conventional, well established processes. These are generally made from sugars, grains, or seeds, i.e. utilize only a specific (often edible) portion of the above-ground biomass produced by a plant. These are often produced with relatively simple processes (United Nations, 2008). Most well-known first generation biofuel is Ethanol produced from fermenting sugars extracted from starch laden crops like sugarcane, sugar beet, corn etc. Using similar processing but a different microbe for fermenting is used to make Butanol.

Pros: Mature technology, familiar feedstock, scalable production capabilities, cost competitive to fossil fuels

Cons: Food vs fuel debate, feedstock price volatility, Low land use efficiency, geographical limitations, modest net reduction in fossil fuel use and greenhouse gas emissions with current processing methods.

2. Second generation: The biofuels produced in this category are generally made from lignocellulosic biomass. This includes either non-edible residues of food crop production (e.g. corn stalks or rice husks) or non-edible whole plant biomass (e.g. grasses or trees grown specifically for energy) (United Nations, 2008). These can be produced from feedstock grown on marginal arable croplands and/or using non-food crops and residues (Biofuels Digest, 2010). These can be further classified based on conversion technology as biochemical and thermochemical. Ethanol is the most common product in this category but competitive production (without subsidies) still needs research (IEA, Bioenergy, 2016).

Pros: Surplus feedstock supply, less controversial, less dependence on geographical location, suitable for developing agrarian countries with large population.

Cons: High capital cost, technological breakthroughs needed, development of high biomass feedstocks to improve land use efficiency.

These two generations of biofuels are the most commonly addressed in academia and industry as of today. Figure 1 summarize production technologies and application of biofuels in replacing petroleum based fuel products.

Figure 1 Substitutability of biofuels (1st and 2nd generations) with common petroleum derived fuels and respective production technologies

First and second generation biofuels have inherent limitations preventing them to from becoming a long term alternative to petroleum. Use of food based feedstocks, competition for scare cropland and fresh water, use of fertilizers, seasonality, and population rise are few of the many (Kagan, 2010). Moreover, these fuels cannot be used above small blends without modifying the engines and have no application in Jet fuel market (a large transportation fuel segment) (Kagan, 2010; Aro, 2016). The advanced biofuels, currently is research stage, aim to fulfill this gap. They can further be divided into two generations.

3. Third generation: Biofuels made using non-arable land, based on integrated technologies that produce a feedstock as well as a fuel (or fuel precursor, such as pure vegetable oil), and require the destruction of biomass. These are similar to the 2nd generation fuels but use lot less resources in generating feedstock. Algae is the most promising feedstock candidate in this category which cannot be matched by any other feedstock in terms of quantity or diversity (Biofuel, 2016). This category is under extensive research to reduce production costs and improve metabolic production of fuels (Aro, 2016).

Pros: Only inputs to get feedstock is CO2 and water. Less controversial, versatile array of products possible.

Cons: High capital costs, early research stage

4. Fourth Generation: This category includes biofuels which can be made using non-arable land. These do not require destruction of biomass to be converted to fuel. This technology aims at directly converting available solar energy to fuel using inexhaustible, cheap and widely available resources. They (photobiological solar fuels and electrofuels) are the most advanced biofuels currently under research (Aro, 2016).

Pros: Only inputs to get feedstock is CO2 and water. Less controversial, versatile array of products possible, least negative environmental impact

Cons: High capital costs, early research stage, long processing time. Slow yields

Food and Agricultural Organization (FAO) classification

FAO uses a comprehensive classification based on nature of feedstock and energy content rather than the conversion technology. This classification covers biofuels on the bases of origin of biomass and important trade forms. The aim to develop such system is to assist in recording trades and production stats across the globe (FAO, 2004). FAO classified biofuels into three common groups, namely, Woodfuels, Agrofuels and Municipal By-products. Figure 2 summarize the classification.

Figure 2. FAO classification of Biofuels (FAO, 2004, p. 9).

Having uniform classification systems are important both for structural innovation and future commercialization of biofuels. Moreover the classification should also be easy to understand and self-explanatory. The two major biofuel classification systems discussed above should help the reader in understanding the global biofuel commercial and underdevelopment market.


  • Aro, E. (2016). From first generation biofuels to advanced solar biofuels. Ambio, 24-31.
  • Biofuel. (2016). Third generation biofuel. Retrieved from
  • Biofuels Digest. (2010, May 18). What are – and who’s making – 2G, 3G and 4G biofuels? Retrieved from Biofuels Digest:
  • IEA. (2011, 4 20). Biofuels can provide up to 27% of world transportation fuel by 2050, IEA report says – IEA ‘roadmap’ shows how biofuel production can be expanded in a sustainable way, and identifies needed technologies and policy actions. Retrieved from International Energy Agency:
  • IEA. (2016, 12 14). Bioenergy. Retrieved from International Energy Agency:
  • Kagan, J. (2010). Third and Forth Generation Biofuels: technologies, markets and economics through 2015. GTM Research.
  • United Nations. (2008). Biofuel Production Technologies: Status, Prospects and Implicatiopns for trade and development. New York: United Nations Conference on Trade and Development.