Abstract
Motivated by a real-life application, this research considers the multi-objective vehicle routing and loading problem with time window constraints which is a variant of the Capacitated Vehicle Routing Problem with Time Windows with one/two-dimensional loading constraints. The problem consists of routing a number of vehicles to serve a set of customers and determining the best way of loading the goods ordered by the customers onto the vehicles used for transportation. The three objectives pertaining to minimisation of total travel distance, number of routes to use and total number of mixed orders in the same pallet are, more often than not, conflicting. To achieve a solution with no preferential information known in advance from the decision maker, the problem is formulated as a Mixed Integer Linear Programming (MILP) model with one objective—minimising the total cost, where the three original objectives are incorporated as parts of the total cost function. A Generalised Variable Neighbourhood Search (GVNS) algorithm is designed as the search engine to relieve the computational burden inherent to the application of the MILP model. To evaluate the effectiveness of the GVNS algorithm, a real instance case study is generated and solved by both the GVNS algorithm and the software provided by our industrial partner. The results show that the suggested approach provides solutions with better overall values than those found by the software provided by our industrial partner.
Highlights
Current trends in international markets such as competition and globalization are forcing all organisations across supply chains to reduce their costs including logistics expenditures through more efficient decision making
3.4.1 Stage one routing with 1D pallet loading. The challenge of this Stage One modelling is that the number of pallets of each type s to be loaded onto the vehicle is unknown in advance
The problem consists of routing a number of routes to serve a set of customers, and determining the best way for loading the goods ordered by the customers on the vehicles used for transportation
Summary
Current trends in international markets such as competition and globalization are forcing all organisations across supply chains to reduce their costs including logistics expenditures (related to travel distance, travel time, holding cost, etc.) through more efficient decision making. Before loading the pallets onto the vehicle, the 3D items ordered by the customers need to. The items of same type ordered by the same customer are recorded by their weights, volumes and numbers rather than their weights, lengths, widths and heights, following the ontology of the Pallet-Packing Vehicle Routing Problem (PPVRP) (Zachariadis et al 2012). Consulting our industrial partner, they favour putting the same orders in the same pallets with as minimum mixture as possible (that is, the same pallet should contain the items from the same customer of same product type).
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