The planning and optimisation of a supply chain network under uncertainty

Cole, Barrie Michael (2015-12)

Thesis (PhD)--Stellenbosch University, 2015.

Thesis

ENGLISH ABSTRACT: This research work addresses the planning and optimisation 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, Such methodology is formulated by identifying methodologies from previous research works for instances of single (e.g. fuzzy optimisation), binary (e.g. fuzzy-multi-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 (NH4NO3), nitrophosphate ((NH4)2SO4, (NH4)H2PO4, NH4NO3, CaSO4.2H2O), superphosphate (40%Ca(H2PO4)2 + 60%CaSO4.2H2O) 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.

AFRIKAANSE OPSOMMING: Hierdie navorsing handel oor die beplanning en optimalisering van verskaffingskettings wat onderworpe is aan die tipiese onseker bedryfsomstandighede van ’n verskaffingskettingomgewing, naamlik newelagtigheid (<, ≤, > of ≥) en stogastiese veranderlikheid (waarskynlikheid). Die beplanningsaspek verwys na ’n behoefte om van tyd tot tyd veelvuldige prestasiemikpunte by die assessering en bestuur van verskaffingskettings in te sluit. Hierdie multi-mikpuntaspek (“multi-objectivity”) dui op die bestaan van veelvuldige maksima, veelvuldige minima of ’n kombinasie van sowel maksima as minima in ’n verskaffingskettingbestuursomgewing. Vorige navorsingswerk oor verskaffingskettings met onseker bedryfsomstandighede het ondersoek ingestel na optimalisering in slegs een of twee scenario’s van bedryfsonsekerheid, en het soms ook die multi-mikpuntvereiste van beplanning ingesluit, byvoorbeeld neweloptimalisering, stogastiese neweloptimalisering of multi-mikpunt- stogastiese neweloptimalisering. Hierdie studie brei uit op daardie vorige werk deur nie net tersaaklike gevalle van bedryfsonsekerheid in ’n verskaffingskettingomgewing in ag te neem nie, maar ook heersende gevalle van multi-mikpuntbeplanning (met ander woorde maksima of minima, of ’n kombinasie daarvan). Slegs op dié manier kan ‘realistiese’ en beplande verskaffingskettingoplossings bedink word, aangesien dit vir alle heersende omstandighede van bedryfsonsekerheid voorsiening maak. ’n Tipiese verskaffingsketting is ’n produksie- en verspreidingsnetwerk wat uit etlike produksiesentrums, verspreidingsfasiliteite en afsetpunte bestaan. Die doel van hierdie studie was die bekendstelling en omskrywing van ’n metodologie vir die optimalisering van verskaffingskettings in ’n kombinasie van onsekerheids- en beplanningsomstandighede, om sodoende die beste bedryfsoplossing vir verskaffingskettings te vind. Hiervoor is die metodologieë uit vorige navorsingstudies oor die eenledige (bv newel-), tweeledige (bv multi-mikpunt-newel-) en drieledige (bv multi-mikpunt- stogastiese newel-) optimalisering van verskaffingskettings bepaal en ontleed, gevolg deur die onttrekking van die reeks optimaliseringstappe wat gebruik is, om ’n omvattende metodologie vir die beplanning en optimalisering van verskaffingskettings met onseker bedryfsomstandighede te skep. Die metodologie is bevestig deur die optimale resultate te vergelyk met dié wat met ’n gevestigde tegniek vir verskaffingskettingoptimalisering behaal is en wat aan dieselfde bedryfsomstandighede onderworpe was. Die twee stelle optimale resultate was presies dieselfde. Hierdie metode is toegepas op die beplanning en optimalisering van ’n fasiliteit vir die produksie en verspreiding van ’n NPK- (stikstof-fosfor en-kalium-)kunsmis. Dié fasiliteit is onderworpe aan newelonsekerheid (<, ≤, >, ≥) in markvraag, en het ook ’n multimikpuntvereiste in bedryfsbeplanning om die produksie en verspreiding van ’n hele reeks NPK-kunsmis ooreenkomstig markvraag te maksimaliseer, en terselfdertyd die ontwikkeling en afvoer van ’n gevaarlike gasagtige waterstoffluoried-afloop uit die nitrofosfaat-produksie-eenheid te beperk. Daar is meer as 15 verskillende soorte NPKkunsmis beskikbaar, en elkeen is bedoel vir ’n bepaalde tipe landbougewas, byvoorbeeld mielies, koring, lusern, ensovoorts. Daarom lei markvraagonsekerheid direk tot produksie-onsekerheid, met onseker grondstoftoekenning wat die verskillende bronne van stikstof (N), fosfor (P) en kalium (K) betref, met ander woorde ammoniumnitraat (NH4NO3), nitrofosfaat ((NH4)2SO4, (NH4)H2PO4, NH4NO3, CaSO4.2H2O), superfosfaat (40%Ca(H2PO4)2 + 60%CaSO4.2H2O) en kaliumchloried (KCl). Met optimale produksie-/verspreidingsresultate is 99,3% van die maksimum moontlike produksie- en verspreidingsvermoë bereik, wat ook met markvraag strook. Daarbenewens is die hipotese bevestig deur die aard van die optimale resultate in die gevallestudie, sowel as deur ’n studie van die rasionaliteit van die resultate toe die beplannings- en bedryfsonsekerheidsomstandighede in die gevallestudie afgewissel is.

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