Imposing Contiguity Constraints in Political Districting Models

For nearly 60 years, operations research techniques have assisted in the creation of political districting plans, beginning with an integer programming model. This model, which seeks compactness as its objective, tends to generate districts that are contiguous, or nearly so, but provides no guarantee of contiguity. In the paper “Imposing contiguity constraints in political districting models” by Hamidreza Validi, Austin Buchanan, and Eugene Lykhovyd, the authors consider and analyze four different contiguity models (two old and two new). Their computer implementation can handle redistricting instances as large as Indiana (1,511 census tracts). Their fastest approach uses a branch-and-cut algorithm, where contiguity constraints are added in a callback. Critically, many variables can be fixed to zero a priori by Lagrangian arguments. All test instances and source code are publicly available.

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

Alongside the rise of ‘last-mile’ delivery in contemporary urban logistics, drones have demonstrate commercial potential, given their outstanding triple-bottom-line performance. However, as a lithium-ion battery-powered device, drones’ social and environmental merits can be overturned by battery recycling and disposal. To maintain economic performance, yet minimise environmental negatives, fleet sharing is widely applied in the transportation field, with the aim of creating synergies within industry and increasing overall fleet use. However, if a sharing platform’s transparency is doubted, the sharing ability of the platform will be discounted. Known for its transparent and secure merits, blockchain technology provides new opportunities to improve existing sharing solutions. In particular, the decentralised structure and data encryption algorithm offered by blockchain allow every participant equal access to shared resources without undermining security issues. Therefore, this study explores the implementation of a blockchain-enabled fleet sharing solution to optimise drone operations, with consideration of battery wear and disposal effects. Unlike classical vehicle routing with fleet sharing problems, this research is more challenging, with multiple objectives (i.e., shortest path and fewest charging times), and considers different levels of sharing abilities. In this study, we propose a mixed-integer programming model to formulate the intended problem and solve the problem with a tailored branch-and-price algorithm. Through extensive experiments, the computational performance of our proposed solution is first articulated, and then the effectiveness of using blockchain to improve overall optimisation is reflected, and a series of critical influential factors with managerial significance are demonstrated.

Investment decision modeling for transboundary project portfolio selection

Joint activities for global water partnerships in regional development programs are usually facilitated by implementing transboundary water projects. Most projects are however hampered by the absence of a clear economic base for making investment decisions. In this paper, we propose a zero-one integer programming model to determine the optimal decisions for selection of project portfolios on transboundary waters; where project selection is based on several time periods in the future.The objective is to determine whether to undertake a project or not; so that the net present value of investment returns is maximized to support needy communities. A numerical example is presented for illustration; demonstrating the optimal choice of investment projects under budget constraints. The zero-one integer programming model provides a feasible solution for choice of transboundary project investment decisions; given the competing nature of capital budgets prior project implementation. The proposed model can be efficient; where limited funds among competing projects serve as a basis for project selection criteria; a decision for facilitation enhancement towards water partnership for regional development.

Scheduling the Main Professional Football League of Argentina

In this paper, we describe our work in scheduling Argentina’s First Division professional football league, the Superliga. Following existing work in sports scheduling, we develop an integer programming model for the Superliga season schedule and then, solve it using a decomposition approach. Unlike previous work, this scheme is based on the creation and assignment of cluster patterns, which take advantage of the model’s geographically driven handling of sporting fairness. We also model the assignment of matches to specific dates and time slots while simultaneously considering various conditions relating to or imposed by game broadcasters, the government, and international tournament calendars. Our work was implemented to schedule the Superliga’s 2018–2019 and 2019–2020 seasons, achieving clear improvements on a number of criteria over the previous approach.