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Using optimisation to suggest alternative supply chains in the context of industrial symbiosis
conference contribution
posted on 2015-12-01, 00:00 authored by F Stock, S Dunstall, M Ayre, A Ernst, Asef NazariAsef Nazari, Dhananjay ThiruvadyDhananjay Thiruvady, S KingThe concept of firms exchanging materials, energy, water, and/or by-products in a collective approach to competitive advantage is called Industrial Symbiosis (IS). It was first described by Frosch and Gallopoulos
in 1989, and in the same year, scientists uncovered an extensively intertwined network of companies from different industries in Kalundborg, Denmark that was a realisation of Frosch and Gallopoulos’ ideas. In IS, an unresolved research question relates to whether IS can be designed “ground up” into an industrial system (such as via planned eco-parks), or whether it can only occur “organically” through more serendipitous
business interactions. Given data on a defined set of businesses, quantified amounts of input and raw materials, and material transformation opportunities, our interest is on the use of computation and optimisation techniques in order uncover the potential for IS amongst firms, and to suggest for a single business which potential partners the business should target in order to build a network that could realise this potential. The transformation opportunities are modelled as processes in which a business, consortium, or external agent (such as a local authority) could invest, to enable materials to be transformed from lower to higher value. Examples might include (re-)manufacturing processes, a shared space for materials aggregation, or compressing and baling machinery that could increase waste density and so reduce storage and transportation costs for a material. To formulate the problem, we consider the potential material flows between businesses and processes, using
a linear distance model to describe transportation costs; market values to describe materials that are desirable inputs, and additional sourcing and sinking costs to obtain materials from outside of the network or dispose of surplus materials to landfill. The model is for a single time span, and as such we need to ensure that process investments do not lead to an amplification effect from the total investment cost not being amortized in the considered period. Results are then presented for each participating business in terms of the origins, destinations and investments that describe the subgraph of material flows that maximises their financial return. For the proposed overall network to be commercially viable, each participant must show a positive return; as such we can demonstrate
the difference between the set of local optima and the potential global optimal decisions, thereby uncovering the ideal opportunities for social or government investment.
in 1989, and in the same year, scientists uncovered an extensively intertwined network of companies from different industries in Kalundborg, Denmark that was a realisation of Frosch and Gallopoulos’ ideas. In IS, an unresolved research question relates to whether IS can be designed “ground up” into an industrial system (such as via planned eco-parks), or whether it can only occur “organically” through more serendipitous
business interactions. Given data on a defined set of businesses, quantified amounts of input and raw materials, and material transformation opportunities, our interest is on the use of computation and optimisation techniques in order uncover the potential for IS amongst firms, and to suggest for a single business which potential partners the business should target in order to build a network that could realise this potential. The transformation opportunities are modelled as processes in which a business, consortium, or external agent (such as a local authority) could invest, to enable materials to be transformed from lower to higher value. Examples might include (re-)manufacturing processes, a shared space for materials aggregation, or compressing and baling machinery that could increase waste density and so reduce storage and transportation costs for a material. To formulate the problem, we consider the potential material flows between businesses and processes, using
a linear distance model to describe transportation costs; market values to describe materials that are desirable inputs, and additional sourcing and sinking costs to obtain materials from outside of the network or dispose of surplus materials to landfill. The model is for a single time span, and as such we need to ensure that process investments do not lead to an amplification effect from the total investment cost not being amortized in the considered period. Results are then presented for each participating business in terms of the origins, destinations and investments that describe the subgraph of material flows that maximises their financial return. For the proposed overall network to be commercially viable, each participant must show a positive return; as such we can demonstrate
the difference between the set of local optima and the potential global optimal decisions, thereby uncovering the ideal opportunities for social or government investment.
