The planning and optimisation of a supply chain network under conditions of uncertainty

Barrie M. Cole, Steven Bradshaw
2016 International Journal of Operational Research  
Declaration By submitting this dissertation electronically, I declare that the entirety of the work contained therein is my own, original work, that I am the sole author thereof (save to the extent explicitly otherwise stated), that reproduction and publication thereof by Stellenbosch University will not infringe any third party rights and that I have not previously in its entirety or in part submitted it for obtaining any qualification. Synopsis This research work addresses the planning and
more » ... imisation of supply chains that are subject to conditions of operational uncertainty, i.e. fuzziness, (<, <, > or >) and stochastic's (probability), that typically exist in a supply chain operational environment. The 'planning' aspect refers to an occasional need to accommodate multiple performance objectives in the assessment and management of supply chains, and this aspect is more commonly referred to as 'multi-objectivity, which means the existence of multiple maxima, multiple minima or a combination of both maxima and minima objectives in a supply chain environment. Previous work on supply chain under uncertainty research had considered optimisation under one or two conditions of operational uncertainty, and sometimes including the planning requirement of multi-objectivity e.g. fuzzy optimisation, stochastic-fuzzy optimisation, multi-objective-stochastic-fuzzy optimisation. This current thesis is an extension of those works by considering not only relevant cases of operational uncertainty but also by considering those prevailing planning instances of multi-objectivity (i.e. maxima or minima or a combination of both maxima and minima) in a supply chain operating environment. Such capability would be tantamount to being able to deliver 'realistic' and planned supply chain solutions since all prevailing conditions of operational uncertainty would have been accommodated. A typical supply chain is a production and distribution network consisting of multiple production centres, distribution facilities and sales outlets. The objective of this work is to introduce and define a methodology for the optimisation of supply chains under prevailing combinational conditions of uncertainty and planning, which would be tantamount to the means of finding the best operating solution for supply chains, Stellenbosch University The Planning and Optimisation of a Supply Chain Network under Uncertainty iv Such methodology is formulated by identifying methodologies from previous research works for instances of single (e.g. fuzzy optimisation), binary (e.g. fuzzymulti-objective optimisation) and ternary (e.g. stochastic-fuzzy-multi-objective optimisation) supply chain under uncertainty methodologies from previous research works, analysing them and then extracting the sequence of optimisation steps utilised. Such extracted optimisation methodologies, to provide a methodology for the planning and optimisation of supply chains, under conditions of uncertainty. The methodology was validated by the comparison of optimum results with those generated by a established supply chain optimisation technique, and that was subject to the same operating conditions. Both sets of optimum results were exactly the same. This method is applied to the planning and optimisation of a NPK fertiliser production and distribution facility, which is subject to fuzzy (<, <, >, >) market demand uncertainty and which also has a multi-objective operational planning requirement to maximise the production and distribution of an entire range of NPK fertiliser in accordance with market demand, as well as to simultaneously minimise the generation and discharge of hazardous Hydrogen Fluoride (HF) gaseous effluent from the NPK fertiliser Nitrophosphate production unit. There are over 15 different blends of NPK (nitrogen, phosphorous, potassium) fertiliser available, with each blend being suited to a particular agricultural crop-type, e.g. maize, wheat, lucerne etc., and therefore the market demand uncertainty is directly translated into production uncertainty with uncertain raw material allocation in terms of the various sources of N, P and K, i.e. ammonium nitrate (NH 4 NO 3 ), nitrophosphate ((NH 4 ) 2 SO 4 , (NH 4 )H 2 PO 4 , NH 4 NO 3 , CaSO 4 .2H 2 O), superphosphate (40%Ca(H 2 PO 4 ) 2 + 60%CaSO 4 .2H 2 O) and potassium chloride (KCl). Optimum production/distribution results revealed an achievement of 99.3% of maximum possible production and distribution capability, and also in accordance with market demand. Further, the hypothesis was satisfied by not only of the nature of the case study optimum results but also by checking the rationality of the results generated from varying the planning and operational uncertainty scenarios in the case study.
doi:10.1504/ijor.2016.078942 fatcat:jz7qdpvn2rh2zhtjncfhe4x66i