Toll competition in highway transportation networks

Within a highway transportation network, the social welfare implications of two different groups of agents setting tolls in competition for revenues are studied. The first group comprises private sector toll road operators aiming to maximise revenues. The second group comprises local governments or jurisdictions who may engage in tax exporting. Extending insights from the public economics literature, jurisdictions tax export because when setting tolls to maximise welfare for their electorate, they simultaneously benefit from revenues from extra-jurisdictional users. Hence the tolls levied by both groups will be higher than those intended solely to internalise congestion, which then results in welfare losses. Therefore the overarching question investigated is the extent of welfare losses stemming from such competition for toll revenues. While these groups of agents are separately studied, the interactions between agents in each group in competition can be modelled within the common framework of Equilibrium Problems with Equilibrium Constraints. Several solution algorithms, adapting methodologies from microeconomics as well as evolutionary computation, are proposed to identify Nash Equilibrium toll levels. These are demonstrated on realistic transportation networks. As an alternative paradigm to competition, the possibilities for co-operation between agents in each group are also explored. In the case of toll road operators, the welfare consequences of competition could be positive or adverse depending on the interrelationships between the toll roads in competition. The results therefore generalise those previously obtained to a more realistic setting investigated here. In the case of competition between jurisdictions, it is shown that the fiscal externality of tax exporting resulting from their toll setting decisions can substantially reduce the welfare gains from internalising congestion. The ability of regulation, co-operation and bilateral bargaining to reduce the welfare losses are assessed. The research thus contributes to informing debates regarding the appropriate level of institutional governance for toll pricing policies

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Solving linear multiplicative programs via branch-and-bound: a computational experience

In this paper, linear multiplicative programs are approached with a branch-and-bound scheme and a detailed computational study is provided. Several underestimation functions are analyzed and various partitioning criteria are presented. A particular class of linear multiplicative programs, useful to solve some applicative bilevel problems, is considered from a theoretical point of view to emphasize an efficient solution method. Detailed results of the computational study are provided to point out the performances provided by using various underestimation functions and partitioning criteria, thus improving some of the results of the current literature

Multi-site capacity planning and business optimisation for process industries.

Changing market conditions, volatile customer demand, intense competition and tightness of capital are some of the primary characteristics of the global economy that affect process industries nowadays. The main objective of the thesis is to facilitate business decision-making in today's increasingly complex and highly uncertain market environment by applying mathematical programming techniques for multi-site capacity planning and business optimisation in process industries. In the first part of the thesis, the problem of multi-site capacity planning under uncertainty in the pharmaceutical industry is addressed. A comprehensive two-stage, multi-scenario mixed-integer linear programming (MILP) model is proposed able to determine an optimal product portfolio and multi-site investment plan in the face of clinical trials uncertainty. A hierarchical algorithm is also developed in order to reduce the computational effort needed for the solution of the resulting large-scale MILP model. The applicability of the proposed solution methodology is demonstrated by a number of illustrative examples. The second part addresses the problem of business optimisation for customer demand management in process industries. A customer demand forecasting approach is developed based on support vector regression analysis. The proposed three-step algorithm is able to extract the underlying customer demand patterns from historical sales data and derive an accurate forecast as demonstrated through a number of illustrative examples. An active demand management approach for close substitute products is also developed based on price optimisation. The proposed methodology is able to determine optimal pricing policies as well as output levels, while taking into consideration manufacturing costs, resource availability, customer demand elasticity, outsourcing and market competition. An iterative algorithm is developed able to determine Nash equilibrium in prices for competing companies as demonstrated by the illustrative examples

Operational research:methods and applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Distributed Coordination and Optimisation of Network-Aware Electricity Prosumers

Electricity networks are undergoing a transformation brought on by new technologies, market pressures and environmental concerns. This includes a shift from large centralised generators to small-scale distributed generators. The dramatic cost reductions in rooftop solar PV and battery storage means that prosumers (houses and other entities that can both produce and consume electricity) will have a large role to play in future networks. How can networks be managed going forward so that they run as efficiently as possible in this new prosumer paradigm? Our vision is to treat prosumers as active participants by developing a mechanism that incentivises them to help balance power and support the network. The whole process is automated to produce a near-optimal outcome and to reduce the need for human involvement. The first step is to design an autonomous energy management system (EMS) that can optimise the local costs of each prosumer in response to network electricity prices. In particular, we investigate different optimisation strategies for an EMS in an uncertain household environment. We find that the uncertainty associated with weather, network pricing and occupant behaviour can be effectively handled using online optimisation techniques using a forward receding horizon. The next step is to coordinate the actions of many EMSs spread out across the network, in order to minimise the overall cost of supplying electricity. We propose a distributed algorithm that can efficiently coordinate a network with thousands of prosumers without violating their privacy. We experiment with a range of power flow models of varying degrees of accuracy in order to test their convergence rate, computational burden and solution quality on a suburb-sized microgrid. We find that the higher accuracy model, although non-convex, converges in a timely manner and produces near-optimal solutions. We also develop simple but effective techniques for dealing with residential shiftable loads which require discrete decisions. The final part of the problem we explore is prosumer manipulation of the coordination mechanism. The receding horizon nature of our algorithm is great for managing uncertainty, but it opens up unique opportunities for prosumers to manipulate the actions of others. We formalise this form of receding horizon manipulation and investigate the benefits manipulative agents can obtain. We find that indeed strategic agents can harm the system, but only if they are large enough and have information about the behaviour of other agents. For the rare cases where this is possible, we develop simple privacy-preserving identifiers that monitor agents and distinguish manipulation from uncertainty. Together, these components create a complete solution for the distributed coordination and optimisation of network-aware electricity prosumers

Operational Research: methods and applications

This is the final version. Available on open access from Taylor & Francis via the DOI in this recordThroughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes