Operational Research: methods and applications

Figures & data

Figure 1. Modelling and realism: a spectrum of model fidelity. Adapted from Morecroft (2015), Chapter 10.

Table 1. Qualitative SD modelling process based on Kunc (2017a).

Modelling process	Qualitative SD
Objective	Understand the feedback structure of the system.
Inputs	Text data obtained through facilitated face-to-face meetings, interview or the interpretation of causal mechanism in reports and from theories.
Process	The modelling process implies the construction of CLD to represent individual and/or group-level interpretations of causal links. Facilitation processes are critical to uncover the causal links.
Outputs	There are three main outputs: learning about the structure of the system, changes in participants perspectives, and agreement on future policies.

Table 2. Quantitative SD modelling process based on Kunc (2017a).

Modelling process	Quantitative SD
Objective	Test a hypothesis about the structure driving the reference mode of a variable.
Inputs	Text data obtained through facilitated face-to-face meetings, interview or the interpretation of causal mechanism in reports and from theories to determine the structure. Numerical data for the model can come from three sources: judgement from experts or managers, numerical data sets and facilitation processes for nonlinear functions.
Process	After defining the boundary of the model, a stock and flow diagram is developed to represent the structure of the system. Equations are formulated for each variable and parameters entered. Testing of the structure and outputs are performed to confirm the model structure replicates the behaviour observed in the key variables.
Outputs	There are three outputs: time series showing performance over time; performance over time of policies or interventions in the system; and learning about the dynamic behaviour of the system.

Table 3. Problems in relief logistics.

Phase	Main problems considered	Main decisions involved	Main concerns
Preparedness and mitigation	Infrastructure and network structuring	Network design	Connectivity
		(mainly for strengthening purposes)
	Risk assessment	Prioritization	Data preparation
		(of roads, buildings, arcs)	for further analysis
	Evacuation planning	Location of gathering points	Traffic
		Allocation of evacuees	Accessibility
		Routing	Evacuation Time
			Behavioral factors
	Shelter location (and allocation)	Selecting among potential locations	Ensuring accesibility
			Shelter utilization
			Infrastructure (Risk)
			Behavioral factors
	Prepositioning	Locating point of distributions	Budget
		Provisioning (of supplies)	Accessibility
		Related supply chain decisions	Fairness
		(supplier selection, allocation and routing)	Speed
			Efficiency
	Supply chain (procurement) planning	Contract design	Quality
			Efficiency
Response	Damage assessment	Demand assessment	Speed
		Infrastructure assessment	Accuracy
	Search and rescue operations	Team formation and allocation	Speed
			Fairness
			Capacity
	Evacuation	Location	Speed
		Allocation	Risk
		Routing
	Shelter management	Location	Physical environment
		Allocation	Risk
		Related supply chain decisions	Accessibility
		(distribution, routing)	Fairness
			Utilization
	Donation management/	Allocation	Fairness
	Resource allocation	Routing	Efficiency
		Inventory Management
Recovery	Debris management	Network design
		Prioritization and scheduling
		(deciding which nodes/arcs to clean first)

Table 4. Application areas of solvers and simulation software.

Subject	Methodology	Application areas
Solver	LP	Transportation, agriculture, manufacturing
	MILP	Logistics, healthcare, network design, pooling, disaster response
	MINLP	Scheduling, telecommunication, energy systems, layout design, network design, portfolio optimization, water systems
	SP	Supply chain planning, production planning, process control and optimisation
Simulation	DES	Manufacturing, network design, healthcare operations, financial systems, inventory management
	SD	Telecommunication, macro- and micro-economics, social systems, ecological systems
	ABS	Stock markets, robotics, epidemiology, game theory, evacuation planning

Figure 2. An actionable framework for service industries: facilities-transformation-usage (adapted from Moeller, 2010)

Morecroft, J. D. W., 2015. Strategic modelling and business dynamics: A feedback systems approach. John Wiley & Sons.

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Kunc, M., 2017a. System dynamics: A soft and hard approach to modelling. In W. K. V. Chan, A. D’Ambrogio, G. Zacharewicz, N. Mustafee, G. Wainer, & E. Page (Eds.), Proceedings of the 2017 Winter Simulation Conference, Las Vegas, NV (pp. 597–606).

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Moeller, S., 2010. Characteristics of services: A customer integration perspective uncovers their value. Journal of Services Marketing, 24 (5), 359–368. https://doi.org/10.1108/08876041011060468

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