Allocation in Practice

How do we allocate scarcere sources? How do we fairly allocate costs? These are two pressing challenges facing society today. I discuss two recent projects at NICTA concerning resource and cost allocation. In the first, we have been working with FoodBank Local, a social startup working in collaboration with food bank charities around the world to optimise the logistics of collecting and distributing donated food. Before we can distribute this food, we must decide how to allocate it to different charities and food kitchens. This gives rise to a fair division problem with several new dimensions, rarely considered in the literature. In the second, we have been looking at cost allocation within the distribution network of a large multinational company. This also has several new dimensions rarely considered in the literature.Comment: To appear in Proc. of 37th edition of the German Conference on Artificial Intelligence (KI 2014), Springer LNC

Redesign of a sustainable food bank supply chain

Thesis submitted for the degree of Doctor of Philosophy in Mathematics Applied to Economics and Management.Food rescue and delivery organizations target concurrently the environmental objective of reduc- ing food waste, and the social objective of supporting underprivileged segments of the population. They secure surplus and about-to-waste food items from producers, manufacturers and retailers, and redistribute them through charitable agencies and parish councils to support the population in need of food assistance. Inspired by the case of the Portuguese Federation of Food Banks, the study ad- dresses the redesign of a food bank supply chain from a multi-dimensional outlook on sustainability. Considering an initial network of food banks, strategic decisions include the opening and closing of food banks, as well as the installation or expansion of storage and transport resources, while tactical decisions comprise the selection of served charities and respective assignment to the operational food banks. Moreover, product flows across the network are also to be determined. The supply chain is formulated as a three-layer network involving the donors, the food banks, and the charities, where multiple products flow in vertical and lateral directions. Based on an extensive literature review, and supported by an in-depth field research, the problem is formulated as a dynamic and capacitated tri-objective mixed-integer linear programming model, accounting for environmental indicators such as the volume of food waste and CO2 emissions, and social metrics assessing, among others, equity, inclusion, and proximity. The tri-objective problem is studied for regional and national supply chain instances, developed to depict real-life based cases. Non-dominated solutions are obtained for the regional instances appealing to the lexicographic ordering method. Relevant managerial insights are derived from the analysis of the lexicographic solutions. Three decomposition based heuristics de- veloped in this study proved to be effective in solving the national instances. Trade-offs between the economic, environmental, and social objectives are discussed, and properties of the mathematical programming model are proven.As organizações de resgate e distribuição "alimentar perseguem paralelamente o objetivo ambiental de redução do desperdício alimentar e o objetivo social de apoio à população carenciada. Estas entidades angariam excedentes alimentares e produtos em vias de deterioração de produtores, indústrias e do comércio a retalho que redistribuem, através de instituições de solidariedade e autarquias locais, a pessoas com carências alimentares. Inspirado no caso da Federação Portuguesa de Bancos Alimentares, este estudo aborda o redesenho de uma cadeia de abastecimento de bancos alimentares numa perspectiva de sustentabilidade multi-dimensional. Considerando uma rede inicial de bancos alimentares, as decisões estratégicas envolvem a abertura e o encerramento de bancos alimentares, bem como a instalação ou expansão da capacidade de armazenamento e de transporte, ao passo que as decisões táticas compreendem a seleção das instituições servidas e a sua afetação a algum dos bancos em operação. Adicionalmente, são também determinados os fluxos de produtos que circulam na rede. A cadeia de abastecimento é formulada como uma rede de três níveis envolvendo os doadores, os bancos alimentares e as instituições beneficiárias. Nesta rede existem fluxos verticais e laterais de produtos. Com base numa extensa revisão bibliográfica e apoiado por um aprofundado trabalho de campo, o problema é formulado como um modelo de programação linear inteira-mista, dinâmico, com capacidades e tri-objetivo. Este problema considera indicadores ambientais como o volume de desperdício alimentar e as emissões de CO2, e como métricas sociais a equidade, a inclusão e a proximidade, entre outros. O problema é estudado para instâncias de cadeias de abastecimento regionais e nacionais, as quais foram desenvolvidas com o objetivo de retratar casos baseados na realidade. São obtidas soluções não dominadas para as instâncias regionais recorrendo ao método lexicográfico, cuja análise revela conclusões relevantes para a gestão. Foram desenvolvidas três heurísticas baseadas em decomposição que provaram ser eficazes na resolução das instâncias nacionais. São discutidos os compromissos existentes entre os objetivos económico, ambiental e social, e provadas propriedades do modelo de programação matemática.N/

INTEGRATED ROUTING MODELS FOR ENHANCED PRODUCT AND SERVICE DELIVERY

Logistics constitutes a key function of modern-day supply chains and an indispensable prerequisite for the support and growth of conventional brick-and-mortar and online businesses. Whether for procurement or delivery purposes, manufacturers and service providers seek efficient and reliable logistical services. A 2014 Bloomberg survey reports that 73% of supply chain managers are experiencing a shift in their attitude towards transportation services; a function they now view as a key element of their business strategy. The advent of new mobile technologies and online platforms, the use of intermodal logistics, and the multiplication of customer-selected delivery options continue to prompt the development of large-scale complex transportation models. The scope of such models can address a single tier of the supply chain or lie at the interface of two tiers when this integration is necessary to reveal important managerial tradeoffs. Such problems require cutting-edge optimization techniques and powerful computing platforms. Given the scale and recurrence of logistical operations, data-driven optimized policies can achieve multi-million dollar savings in cost and significant improvement in service level. This dissertation develops, in its three essays, specialized algorithms for solving two integrated routing problems that have applications in bi-level transportation. Essay One proposes an exact branch-cut-and-price algorithm for the generalized vehicle routing problem (GVRP) which has applications in maritime transportation, survivable telecommunication network design, and health-care logistics. Decomposition techniques are used to reformulate the GVRP as a set-partitioning model which prompts the development of a column generation approach. A specialized dynamic programming algorithm is proposed for solving the pricing subproblem. The performance of the proposed algorithm is significantly improved by enforcing a set of rounded capacity valid inequalities. Computational results show that the proposed algorithm compares favorably against the state-of-the-art exact algorithm for the GVRP and closes 8 out of 9 previously open GVRP instances in the literature. Essay Two investigates a variant of the Vehicle Routing-Allocation Problem that arises in the distribution of pallets of goods by a food bank to a network of relatively distant nonprofit organizations. Vehicles are routed to selected intermediate delivery sites to which the nonprofit organizations travel to collect their demand. The logistical cost is shared and the objective is to minimize a weighted average of the food bank vehicle routing cost and the travel cost of the nonprofit organizations. We develop an efficient multi-start heuristic that iteratively constructs initial solutions to this problem and subsequently explores their neighborhoods via local improvement and perturbation schemes. In our experience, the proposed heuristic substantially outperforms alternative optimization-based heuristics in the literature in terms of the solution quality and computational efficiency and consistently yields solutions with an optimality gap of 0.5% on average. Essay Three develops an effective branch-and-price algorithm for the aforementioned food bank vehicle routing problem. The pricing subproblem is solved, exactly or heuristically, using a specialized labeling type dynamic programming (DP) algorithm. The computational efficacy of this DP approach stems primarily from the inclusion of preprocessing routines that enhance the label extension scheme by iteratively eliminating dominated (partial) solutions. The proposed exact DP algorithm, and five proposed heuristic variants, significantly reduce the computational time associated with the solution of the pricing subproblem (as opposed to solving the latter as a mixed-integer model with CPLEX). The resulting speedup enables the implementation of a branch-and-price algorithm that greatly outperforms the use of CPLEX over a test-bed of 60 problem instances

An Introduction to Temporal Optimisation using a Water Management Problem

Optimisation problems usually take the form of having a single or multiple objectives with a set of constraints. The model itself concerns a single problem for which the best possible solution is sought. Problems are usually static in the sense that they do not consider changes over time in a cumulative manner. Dynamic optimisation problems to incorporate changes. However, these are memoryless in that the problem description changes and a new problem is solved - but with little reference to any previous information. In this paper, a temporally augmented version of a water management problem which allows farmers to plan over long time horizons is introduced. A climate change projection model is used to predict both rainfall and temperature for the Murrumbidgee Irrigation Area in Australia for up to 50 years into the future. Three representative decades are extracted from the climate change model to create the temporal data sets. The results confirm the utility of the temporal approach and show, for the case study area, that crops that can feasibly and sustainably be grown will be a lot fewer than the present day in the challenging water-reduced conditions of the future

Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling

In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects

Metaheuristic Approaches For Estimating In-Kind Food Donations Availability And Scheduling Food Bank Vehicles

Food banks provide services that allow households facing food insecurity to receive nutritious food items. Food banks, however, experience operational challenges as a result of constrained and uncertain supply and complex routing challenges. The goal of this research is to explore opportunities to enhance food bank operations through metaheuristic forecasting and scheduling practices. Knowledge discovery methods and supervised machine learning are used to forecast food availability at supermarkets. In particular, a quasi-greedy algorithm which selects multi-layer perceptron models to represent food availability is introduced. In addition, a new classification of the vehicle routing problem is proposed to manage the distribution and collection of food items. In particular, variants of the periodic vehicle routing problem backhauls are introduced. In addition to discussing model formulations for the routing problems, a hybrid genetic algorithm is introduced which finds good solutions for larger problem instances in a reasonable computation time