Hybrid simulation optimisation modelling for integrated planning of cash and material flows in supply chains

  • Ehsan Badakhshan

Student thesis: Doctoral Thesis

Abstract

Supply chains are composed of suppliers, manufacturers, distributors, and retailers that are integrated with regard to the physical, financial, and information flows across the supply chain networks. Considering the financial flow within supply chain models is of paramount importance as implementing the supply chain decisions relies on the availability of the financial resources. For instance, opening a new facility in the supply chain network is impossible unless the funding mechanism is explicit.
​​​​​​​This research aims to incorporate financial flow modelling into the supply chain models to ensure that the financial resources are available to the supply chain members at the right time while the profitability of the supply chain is maximized. It provides new insights into the methods to monitor the flow of cash within supply chain networks. It further provides a more realistic view to supply chain total cost by considering the cash holding cost as a constituent of the total cost. To analyse and optimise the performance of the studied supply chains in this research, Hybrid simulation optimisation modelling is used as the modelling approach as it is an effective tool to accommodate uncertainties in internal and external factors to the supply chains, conflicting objectives related to the responsiveness and efficiency of the supply chain, and delays in the supply chain product, information, and cash flows.
To distribute the financial resources fairly among supply chain members, two simulation-based optimisation (SBO) models are developed. The first model is a multi-objective model which contains the minimization of the cash cycle for supply chain members and the second model is a single-objective model that considers the cash cycle of the supply chain as objective function. The two models are optimised through finding the optimal values to the inventory and financial decisions parameters. The results indicated that the cash cycle of the supply chain members and the cash cycle of the supply chain can be decreased significantly by identifying the optimal values to the inventory and financial decisions parameters.
To minimize the inventory of the products at supply chain facilities and match the flow of cash with the demand of the supply chain members under economic uncertainty, an SBO model is developed. The developed model aims to minimize the bullwhip effect, cash flow bullwhip, and supply chain total cost through finding the optimal values to the inventory and financial decisions parameters. The results showed that the SBO model is an effective tool in managing the trade-offs between objective functions as it significantly improved the values of the objective functions compared to the simulation modelling.
To manage the trade-off between profitability and cash cycle in a manufacturing supply chain under economic uncertainty, an SBO model is developed. The developed model aims to minimize cash conversion cycle and maximize economic value-added through finding the optimal values to the production, inventory, and financial decisions parameters. The results showed the superiority of the SBO approach over simulation modelling.
Finally, to maximize the profitability of a manufacturing supply chain in an integrated supply chain network design, supplier selection, and asset-liability management problem under economic uncertainty, a hybrid analytical-SBO model is developed. The developed model aims to maximize the economic value added through finding the optimal values to the manufacturing, inventory, financial, and distribution decisions. The results showed that the hybrid approach outperforms the individual analytical and SBO approaches.
Date of AwardDec 2020
Original languageEnglish
SupervisorLiam Maguire (Supervisor), Ronan Mc Ivor (Supervisor) & Paul Humphreys (Supervisor)

Keywords

  • Simulation-optimization
  • Supply chain finance
  • System dynamics
  • Simulation-based optimization
  • Bullwhip effect

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