A multi-objective optimization tool for the Malawian tea industry with sustainability considerations

Taulo, John Loti (2017-03)

Thesis (PhD)--Stellenbosch University, 2017.

Thesis

ENGLISH ABSTRACT:Corporate social responsibility (CSR) is fast becoming imperative for corporate governance in industry and business worldwide and is assuming an increasingly prominent role in the general discourse on globalization and sustainable development. The World Business Council for Sustainable Development has defined CSR “as the continuing commitment by business to behave ethically and contribute to economic development while improving the quality of life of the workforce and their families as well as of the local community and society”. Different countries and organizations agree on the fundamental principles and spirit embedded in this definition. The major challenge, however, is that there are currently no standardised modalities by which it should be achieved nor a yardstick by which compliance can be graded. Differing perceptions of CSR have resulted in many disparate codes where they exist. In Africa, this problem is further exacerbated by a lack of awareness. In addition, there is an absence of a comprehensive management framework that would address, balance and integrate triple bottom-line considerations. This dissertation primarily aims to address this gap. A tool to support this objective has been proposed, designed and tested in the field. The Malawian tea industry has been identified as a case study. A multitude of challenges in this industry includes child labour and deforestation as well as dwindling product quality and profit margins. These objectives have conflicting demands. The primary objective of this dissertation is to develop a multi-objective optimization tool to support decision-making processes in the Malawian tea industry. This work presents a novel decision support tool, called MOISAT (multi-objective optimization and integrated sustainability assessment tool), for the optimization of operating production processes while minimizing cost impacts and maximizing the long-term sustainability. MOISAT is based on a combination of life cycle analysis (LCA), multi-criteria analysis (MCA), particularly, the analytic hierarchy process (AHP), and non-dominated sorting genetic algorithm (NSGA-II). LCA–based framework methodology is used to quantify the environmental, social and economic sustainability performance of tea production. AHP is applied to evaluate and rank different alternatives based on the judgment of decision makers. NSGA-II, an increasingly popular multi-objective optimization technique is employed to obtain a set of Pareto optimal solutions. The developed tool is empirically tested on a case study of three tea companies in Malawi. Moreover, the applicability of the developed tool has been validated using usability testing, conducted through questionnaire survey and in-depth semi-structured interviews with eight decision makers as well as face to face discussions with experts. The results have demonstrated the usefulness of the tool in pinpointing environmental and social sustainability hot spots within the tea production life cycle stages that need further improvement. Furthermore, the results from this study have shown that the proposed algorithm is effective and has great potential to solve multi-objective optimization problems in the tea industry. Finally, the findings of this study will help decision makers in the tea industry to incorporate sustainability considerations into tea products, processes and activities.

AFRIKAANSE OPSOMMING: Korporatiewe sosiale verantwoordelikheid (KSV) is vinnig besig om noodsaaklik vir korporatiewe bestuur in die industriële- en besigheidswêreld te word en neem ʼn toenemend prominente rol in die algemene diskoers oor globalisering en volhoubare ontwikkeling in. Die Wêreld Besigheidsraad vir Volhoubare Ontwikkeling het KSV gedefinieer as die voortgesette toewyding deur ʼn besigheid om eties op te tree en tot ekonomiese ontwikkeling by te dra, terwyl die lewensgehalte van die arbeidsmag, hul gesinne, die plaaslike gemeenskap asook die samelewing in die algemeen verbeter word. Verskillende lande en organisasies stem saam oor die grondbeginsels en goeie gees wat in hierdie definisie omsluit word. Die groot uitdaging is egter dat daar tans geen gestandaardiseerde modaliteite bestaan waardeur dit bereik kan word nie en ook geen maatstaf waarteen nakoming gegradeer kan word nie. Verskillende persepsies van KSV het tot gevolg gehad dat baie uiteenlopende kodes bestaan. In Afrika, is hierdie probleem verder vererger deur 'n gebrek aan bewustheid. Daarbenewens is daar is 'n gebrek aan 'n omvattende bestuursraamwerk wat drievoudige oorwegings aanspreek, balanseer en integreer. Dit verhandeling is hoofsaaklik daarop gemik om aandag aan hierdie gaping te skenk. 'n Instrument om hierdie doelwit te ondersteun is voorgestel, ontwerp en in die praktyk getoets. Die Malawiese teebedryf is as gevallestudie geïdentifiseer. Menige uitdagings in die bedryf sluit kinderarbeid en ontbossing en kwynende gehalte van die produk en winsmarges in. Hierdie doelwitte het botsende eise. Die hoofdoel van hierdie verhandeling is om ʼn veeldoelige optimaliseringsinstrument om besluitnemingsprosesse te ondersteun in die Malawiese teebedryf te ontwikkel. Hierdie werk bied 'n nuwe besluitondersteuningsgereedskap, genaamd MOISAT (Multi-objective Optimization and Integrated Sustainability Assessment Tool), vir optimale werkproduksieprosesse, terwyl die minimalisering van koste-impak en die maksimering van die langtermyn-volhoubaarheid plaasvind. Die instrument is gebaseer op 'n kombinasie van lewensiklusontleding (LSO), multi-kriteria-analise (MKA), veral die analitiese hiërargiese proses (AHP), en veeldoelige optimeringsmetodes. LSO gebaseerde raamwerk metodes word gebruik om die omgewings-, maatskaplike en ekonomiese volhoubaarheidsprestasie van teeproduksie te kwantifiseer. AHP word toegepas om te evalueer en lys volgens rang verskillende alternatiewe gebaseer op die oordeel van besluitnemers. Nie-gedomineerde sorterings genetiese algoritme (NSGA-II), is 'n toenemende gewilde veeldoelige optimiseringstegniek en word gebruik om 'n stel van Pareto optimale oplossings te kry. Die ontwikkelde instrument is empiries getoets op 'n gevallestudie van drie teemaatskappye in Malawi. Daarbenewens is die toepaslikheid van die ontwikkelde instrument goedgekeur met behulp van ʼn gebruikerstoets wat deur middel van vraelyste en diepgaande semi-gestruktureerde onderhoude met agt besluitnemers, asook gesprekke van aangesig tot aangesig met kundiges uitgevoer is. Die resultate het die nut van die instrument gedemonstreer deur die vasstelling van omgewings- en sosiale volhoubaarheidsbrandpunte binne die teeproduksielewensiklusstadiums wat verdere verbetering nodig het. Verder het die resultate van hierdie studie getoon dat die voorgestelde algoritme effektief is en 'n groot potensiaal vir die oplossing van 'n veeldoelige optimeringsprobleem in die tee-industrie inhou. Die bevindinge van hierdie studie sal besluitnemers in die tee-industrie help om volhoubaarheidsoorwegings te neem in tee produkte, prosesse en aktiwiteite.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/101269
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