An Adaptive Data-Driven Approach to Solve Real-World Vehicle Routing Problems in Logistics

Pseudocode 1

Steps of the proposed algorithm.

	/∗ Prestep (3.1.1) ∗/
	ConnectingToTheDatabase (connection);
	DataInitialization (customersList, vehiclesList, depot, sdvrpConstraints);
	PreparationOfTheInputData (customersList, vehiclesList, depot, sdvrpConstraints);
	TimeWindowsTranspformations (customersList);
	RoutesInitialization (customersList, routes);
	/∗ First step (3.1.2) and (3.1.3) ∗/
	//initial solution becomes optimal routes
	ClarkeWrightSavingsAlgorihm (routes, vehiclesList);
	AssigningVehiclesToRoutes (routes, vehiclesList);
	/∗ Second step (3.1.4) ∗/
	initialSolution = ReducingTheNumberOfRoutes (routes, customersList, vehiclesList);
	/∗ Third step (3.1.5) ∗/
	//the initial solution marked as the initialSolution becomes the optimal routes
	TabuSearch (initialSolution, customersList, vehiclesList, sdvrpConstraints);
	/∗ Fourth step (3.1.6) ∗/
	RoutesOptimization();
	RoutesOptimization2Customers();
	RoutesOptimization3Customers();
	InverseTransformation (customersList, initialSolution);
	/∗ Final step ∗/
	//the result of the fourth step, RouteResList, is the optimal list of routes by vehicle
	StoreOptimalRoutesInTheDatabase (RouteResList);