Vehicle Loading and Routing for Sustainable Transportation: Models and Algorithms

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Vega-Mejía, Carlos Alberto (2018) Vehicle Loading and Routing for Sustainable Transportation: Models and Algorithms. PhD thesis, Victoria University.

Abstract

Two of the most important supply chain activities are the planning and improvement of the packing and distribution of products. These can be studied by means of Vehicle Routing Problems (VRPs) and Packing Problems (PPs). Analyzing these operations separately, and considering only economic aspects, may result in impractical solutions and in overlooking the environmental and social aspects of distribution activities. With the aim of addressing these issues, this thesis presents optimization models and computational solution procedures for the Vehicle Routing Problem with Loading Constraints (VRPLC), considering economic, environmental and social aspects (i.e. the Triple-Bottom-Line (TBL) objectives for sustainability). It also analyzes the effect of these aspects on routing and packing decisions. The thesis starts with a systematic review of the PP, VRP and VRPLC literature, to identify commonly used objective functions and constraints. These are then linked to the three TBL dimensions. This is followed by the formulation of a VRPLC model, which considers optimization criteria and operational constraints that have not been considered simultaneously in previous studies. Although the model can be used to solve problems of small size, large-sized instances can be computationally intractable and require the use of an alternative solution method. In this regard, an efficient hybrid heuristic procedure, which combines a Greedy Randomized Adaptive Search Procedure and a Clarke and Wright Savings Algorithm, is developed to solve the initial model. To specify a more relevant VRPLC application, which is efficient not only in economic terms but in environmental and social criteria as well, these initial findings are then used in the formulation of a VRPLC+TBL model. This extends the VRPLC model to consider the TBL dimensions in terms of profits, fuel consumption, safety features for driving on roads, and equitable distribution of the total payload across the vehicle fleet. Assigning the same payload to each driver, however, may not be possible and worker dissatisfaction may arise due to unfair workload assignments. Using the concepts of Simheuristics, the VRPLC+TBL model is integrated with the design of incentive contracts, to provide a mechanism to compensate workload imbalances and to further extend the social dimension. Overall, this thesis makes a significant contribution to the body of knowledge of routing and loading operations by providing comprehensive models and efficient computational solution procedures that are easy to implement. It also addresses some of the gaps identified in the area of sustainable supply chain management related to the development of quantitative models, heuristic methods, and the simultaneous consideration of all three TBL dimensions. Finally, the thesis proposes some interesting ideas for further research.

Additional Information

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Item type Thesis (PhD thesis)
URI https://vuir.vu.edu.au/id/eprint/39521
Subjects Historical > FOR Classification > 0915 Interdisciplinary Engineering
Historical > FOR Classification > 1503 Business and Management
Current > Division/Research > Institute for Sustainable Industries and Liveable Cities
Keywords supply chain; vehicle routing problems; packing problems; vehicle routing problem with loading constraints; VRPLC; packing; triple-bottom-line; sustainability; transportation; optimization
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