Showing papers by "Dylan Jones published in 2019"

Advances and New Orientations in Goal Programming

Abstract: This chapter starts by providing a categorization of current goal programming literature by type of variant used. Subsequently, goal programming is presented as a secondary model of a general p-metric distance function primary model. This orientation allows us to link goal programming with several fields like the determination of social choice functions or the interpretation and implementation of the Simonian concepts of bounded rationality and “satisficing”. To undertake the latter task, this epistemic framework is understood as a Laudian “Research Tradition” instead of the usual understanding as a scientific theory. Finally, potential future developments to expand the use and flexibility of goal programming as well as to explore possible logical connections of goal programming with other decision-making areas are highlighted.

Formulation and solution of a two-stage capacitated facility location problem with multilevel capacities

Abstract: In this paper, the multi-product facility location problem in a two-stage supply chain is investigated. In this problem, the locations of depots (distribution centres) need to be determined along with their corresponding capacities. Moreover, the product flows from the plants to depots and onto customers must also be optimised. Here, plants have a production limit whereas potential depots have several possible capacity levels to choose from, which are defined as multilevel capacities. Plants must serve customer demands via depots. Two integer linear programming (ILP) models are introduced to solve the problem in order to minimise the fixed costs of opening depots and transportation costs. In the first model, the depot capacity is based on the maximum number of each product that can be stored whereas in the second one, the capacity is determined by the size (volume) of the depot. For large problems, the models are very difficult to solve using an exact method. Therefore, a matheuristic approach based on an aggregation approach and an exact method (ILP) is proposed in order to solve such problems. The methods are assessed using randomly generated data sets and existing data sets taken from the literature. The solutions obtained from the computational study confirm the effectiveness of the proposed matheuristic approach which outperforms the exact method. In addition, a case study arising from the wind energy sector in the UK is presented.

An optimisation model for scheduling the decommissioning of an offshore wind farm

Abstract: An optimisation model is proposed for scheduling the decommissioning of an offshore wind farm in order to minimise the total cost which is comprised of jack-up vessel, barge (transfer) vessel, inventory, processing and on-land transportation costs. This paper also presents a comprehensive review of the strategic issues relating to the decommissioning process and of scheduling models that have been applied to offshore wind farms. A mathematical model using integer linear programming is developed to determine the optimal schedule considering several constraints such as the availability of vessels and planning delays. As the decommissioning problem is challenging to solve, a matheuristic approach based on the hybridisation of a heuristic approach and an exact method is also proposed to find near optimal solutions for a test set of problems. A set of computational experiments has been carried out to assess the proposed approach.

Development and evaluation of a matheuristic for the combined beam angle and dose distribution problem in radiotherapy planning

Abstract: Radiotherapy planning is vital for ensuring the maximum level of effectiveness of treatment. In the planning task, there are at least two connected decision problems that can be modelled and solved using operational research techniques: determining the best position of the radiotherapy machine (beam angle problem) and the optimal dose delivered through each beam (dose distribution problem). This paper presents a mathematical optimization model for solving the combined beam angle and dose distribution problems in the presence of multiple objectives. A matheuristic based on Tabu Search (called TSrad) is developed to solve realistic large-scale instances. The performance of the proposed method is assessed on two prostate cancer instances, namely a single computed tomography (CT) slice and a set of CT slices (three-dimensional problem). For the single-slice problem, the results of TSrad are compared to the optimal solutions obtained by an exact method. Our experiments show that TSrad is able to achieve optimality for some instances. For the multi-slice problem, our experiments show that TSrad produces viable solutions that can be attained in a reasonable computational time.

Making the most out of renewable energy opportunities: Lessons learned from a regional strategic mapping approach

Abstract: Purpose Offshore renewable energy technologies provide many new opportunities for coastal regions around the world, and although the energy policy literature has documented the success stories of many “first mover” regions, there is little guidance for “second mover” or “follower” regions. This paper aims to investigate the strategic challenges faced by coastal regions in the Channel area that are not first movers. Design/methodology/approach The authors use a multiple case study approach to analyse the behaviour of regional stakeholders when planning and assessing their participation in the renewable energy sector. Findings The paper reveals the tendency of regional planners to idealise investments in renewable energy. The negative consequences of idealisation are inadequate strategic visions. Research limitations/implications The findings are only relevant in the context of the regions that are part of the case study. Practical implications The paper illustrates how idealisation of technology or strategy is created and how it impacts strategic decision-making. It also discusses how to address idealisation. Social implications Although much of the energy policy literature discusses the challenge of social acceptance, this paper documents an opposite phenomenon, idealisation. There is a need in the energy sector to find a middle ground between these two extremes. Originality/value The paper provides evidence and a theoretical analysis of a decision-making bias, idealisation, which is not discussed in the literature.

Optimal location of novel robotic prostrate cancer biopsy and brachytherapy treatment devices

Abstract: This paper details research towards the optimal placement of a novel robotic device for the detection and treatment of prostate cancer, via biopsy and brachytherapy respectively. A methodology for analysis of available data in order to determine geographical areas with relatively high prevalence of prostate cancer and low access to treatment is proposed. Areas in the South of the UK with high values of these indices are highlighted. The development of single and multiple criteria optimization models based on the new metric in order to optimally locate a small number of future prototype treatment devices is discussed. Discussions, conclusions and avenues for future research are given.

Um Modelo de Programação por Metas Estendido para o Planejamento de Radioterapia

Abstract: Neste artigo e proposto um modelo de programacao por metas estendido aplicado ao planejamento de radioterapia , em que foi encontrada a melhor combinacao de pesos para as metas a serem atingidas . O modelo foi aplicado a um caso real de câncer de prostata e resolvido pelo software CPLEX , em que foi utilizado o Metodo de Pontos Interiores Barreira Logaritmica como metodo de resolucao .