A survey of current continuous nonlinear multi-objective optimization (MOO) concepts and methods is presented. It consolidates and relates seemingly different terminology and methods. The methods are divided into three major categories: methods with a priori articulation of preferences, methods with a posteriori articulation of preferences, and methods with no articulation of preferences. Genetic algorithms are surveyed as well. Commentary is provided on three fronts, concerning the advantages and pitfalls of individual methods, the different classes of methods, and the field of MOO as a whole. The Characteristics of the most significant methods are summarized. Conclusions are drawn that reflect often-neglected ideas and applicability to engineering problems. It is found that no single approach is superior. Rather, the selection of a specific method depends on the type of information that is provided in the problem, the user’s preferences, the solution requirements, and the availability of software.

Survey of multi-objective optimization methods for engineering

Multi-objective optimization using genetic algorithms: A tutorial

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

An extension of TOPSIS for group decision making

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Linear And Nonlinear Programming

In this paper a matheuristic using a combined Genetic Algorithm (GA) and exact method approach is proposed for selecting the position of the beams and dose distribution in Intensity Modulated Radiotherapy Planning (IMRT). GA selects a set of beams, for which the dose distribution is determined in the process of the GA's evaluation, using an optimisation model that is solved by an Interior Point method. Two instances are used to evaluate the performance of the matheuristic, comparing to the optimum solution, in terms of solution and computation time, found using the exact methodology of Branch and Bound. The results show that the matheuristic is appropriate to this problem in the case study proposed, as it is extremely faster than the exact method and also have reached the optimum solution in several experiments done.

/pdf/a-matheuristic-for-the-selection-of-beam-directions-and-dose-3sf6rr1gqk.pdf

A matheuristic for the selection of beam directions and dose distribution in Radiotherapy Planning

Water Transportation is the cheapest transportation mode, which allows the transfer of very large volumes of cargo between continents. One of the most important types of ships used to transfer goods are the Container Ships, therefore, containerized trade volume is rapidly increasing. This has opened a number of challenging combinatorial optimization problems in container terminals. This paper focuses on the integrated problem Berth Allocation and Quay Crane Assignment Problem (BQ-CAP), which occur while planning incoming vessels in container terminals. We provide a Genetic Programming (GP) approach to evolve effective and robust composite dispatching rules (CDRs) to solve the problem and present a comparative study with the current state-of-art optimal approaches. The Computational results disclose the effectiveness of the presented approach.

/pdf/evolving-local-search-heuristics-for-the-integrated-berth-1g3gat6ell.pdf

Evolving local search heuristics for the integrated berth allocation and quay crane assignment problem

CoBra robot for localized cancer treatment and diagnosis under real-time MRI

Post-warranty maintenance strategy selection using shape packages process

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.

Dylan Jones

Papers

A matheuristic for the selection of beam directions and dose distribution in Radiotherapy Planning

Evolving local search heuristics for the integrated berth allocation and quay crane assignment problem

CoBra robot for localized cancer treatment and diagnosis under real-time MRI

Post-warranty maintenance strategy selection using shape packages process

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