The search : version 1

The Search (version 1) is one of a suite of drawings that responds to the work 'Kangaroo Stalking' by S.T.Gill. It also plays with certain ideas or problems in the depiction of landscape more broadly. The exhibition invited SCCA staff to each respond to a particular work within the Deakin collection.

Solving a multiobjective job shop scheduling problem using Pareto Archived Cuckoo Search

This paper investigates a new approach for solving the multiobjective job shop scheduling problem, namely the Cuckoo Search ( CS) approach. The requirement is to schedule jobs on a single machine so that the total material waste is minimised as well as the total tardiness time. The material waste is quantified in terms of saving factors to show the reduction in material that can be achieved when producing two jobs with the same materials in sequence. The estimated saving factor is used to calculate a cost savings for each job based on its material type. A formulation of multiobjective optimisation problems is adopted to generate the set of schedules that maximise the overall cost savings and minimise the total tardiness time. where all trade-offs are considered for the two conflicting objectives. A Pareto Archived Multiobjective Cuckoo Search (PAMOCS) is developed to find the set ofnondominated Pareto optimal solutions. The solution accuracy of PAMOCS is shown by comparing the closeness of the obtained solutions to the true Pareto front generated by the complete enumeration methad. Results shaw that CS is a very effective and promising technique to solve job shop scheduling problems.

In search of best practices in responsible gambling ( RG ) : a report on a comparative study of RG among Macau, Las Vegas, and Melbourne, presented to the MSAR Bureau of Gaming Inspection and Coordination (DICJ).

This is a project sponsored by the Asia Pacific Association for Gambling Studies (APAGS) and supported by funds from the MSAR’s Bureau of Gambling Inspection and Coordination (DICJ). The research team comprises as Chief Investigators: Prof. Zhidong Hao of the University of Macau; Prof. Linda Hancock of Deakin University, Australia, and Prof. William Thompson, University of Las Vegas (UNLV). The project research was conducted between the end of December 2012 and July 2013.
The starting point for the research was to select four out of the six casino companies licensed to operate in Macau that also operate transnationally, that is, either in Las Vegas or Melbourne. Hence, the Venetian, Wynn, MGM, and the Melco-Crown Entertainment are the focus of research. The main objectives of the project are to explore how responsible gambling is framed in each of the three jurisdictions (Macau, Las Vegas and Melbourne); how it is approached cross-jurisdictionally by each of the companies; and to assess current approaches within a broader comparative context against international best practice. The research explores Responsible Gambling measures taken by a range of stakeholders including the government/regulators in each of the three jurisdictions, casino managements, problem gambling counselling services, unions and community organizations. The research emphasizes what problems prevail, and the implications of this research for enhancing Responsible Gambling in Macau.

A modified Intelligent Water Drops algorithm and its application to optimization problems

The Intelligent Water Drop (IWD) algorithm is a recent stochastic swarm-based method that is useful for solving combinatorial and function optimization problems. In this paper, we investigate the effectiveness of the selection method in the solution construction phase of the IWD algorithm. Instead of the fitness proportionate selection method in the original IWD algorithm, two ranking-based selection methods, namely linear ranking and exponential ranking, are proposed. Both ranking-based selection methods aim to solve the identified limitations of the fitness proportionate selection method as well as to enable the IWD algorithm to escape from local optima and ensure its search diversity. To evaluate the usefulness of the proposed ranking-based selection methods, a series of experiments pertaining to three combinatorial optimization problems, i.e., rough set feature subset selection, multiple knapsack and travelling salesman problems, is conducted. The results demonstrate that the exponential ranking selection method is able to preserve the search diversity, therefore improving the performance of the IWD algorithm. © 2014 Elsevier Ltd. All rights reserved.

Tree-based iterated local search for Markov random fields with applications in image analysis

The maximum a posteriori assignment for general structure Markov random fields is computationally intractable. In this paper, we exploit tree-based methods to efficiently address this problem. Our novel method, named Tree-based Iterated Local Search (T-ILS), takes advantage of the tractability of tree-structures embedded within MRFs to derive strong local search in an ILS framework. The method efficiently explores exponentially large neighborhoods using a limited memory without any requirement on the cost functions. We evaluate the T-ILS on a simulated Ising model and two real-world vision problems: stereo matching and image denoising. Experimental results demonstrate that our methods are competitive against state-of-the-art rivals with significant computational gain.

Development of guidelines for adults on how to communicate with adolescents about mental health problems and other sensitive topics: a Delphi study

There is little evidence-based information available to guide adults in the general community on communicating effectively with adolescents about mental health problems or other sensitive topics. The Delphi methodology was used to develop guidelines to fill this evidence gap. An online questionnaire containing potential guideline statements was developed following a literature search and input from two focus groups. Two expert panels (Youth Mental Health First Aid instructors and young consumer advocates) rated the questionnaire over three rounds, according to whether or not they believed that the statements should be included in the guidelines. Results were analyzed by comparing endorsement rates between the panels. Of the 175 statements presented, 80 were rated as essential or important by ≥90% of both panels and were included in the guidelines. The Delphi process has offered an effective way to achieve consensus between expert panels on useful tips to help adults communicate with adolescents.

Parent and family factors associated with service use by young people with mental health problems: a systematic review

AIM: To conduct a systematic review of parent and family factors associated with service use for young people with mental health problems, to inform early intervention efforts aimed at increasing service use by young people. METHODS: A systematic search of academic databases was performed. Articles were included in the review if they had: a sample of young people aged between 5 and 18 years; service use as the outcome measure; one or more parental or family variables as a predictor; and a comparison group of non-service using young people with mental health problems. In order to focus on factors additional to need, the mental health symptoms of the young person also had to be controlled for. Stouffer's method of combining P-values was used to draw conclusions as to whether or not associations between variables were reliable. RESULTS: Twenty-eight articles were identified investigating 15 parental or family factors, 7 of which were found to be associated with service use for a young person with mental health needs: parental burden, parent problem perception, parent perception of need, parent psychopathology, single-parent household, change in family structure and being from the dominant ethnic group for the United States specifically. Factors not found to be related to service use were: family history of service use, parent-child relationship quality, family functioning, number of children, parent education level, parent employment status, household income and non-urban location of residence. CONCLUSIONS: A number of family-related factors were identified that can inform effective interventions aimed at early intervention for mental health problems. Areas requiring further research were also identified.

Graphical constraints: a graphical user interface for constraint problems

A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embraces areas like resource allocation, scheduling, timetabling or vehicle routing. Constraint programming is a form of declarative programming in the sense that instead of specifying a sequence of steps to execute, it relies on properties of the solutions to be found, which are explicitly defined by constraints. The idea of constraint programming is to solve problems by stating constraints which must be satisfied by the solutions. Constraint programming is based on specialized constraint solvers that take advantage of constraints to search for solutions. The success and popularity of complex problem solving tools can be greatly enhanced by the availability of friendly user interfaces. User interfaces cover two fundamental areas: receiving information from the user and communicating it to the system; and getting information from the system and deliver it to the user. Despite its potential impact, adequate user interfaces are uncommon in constraint programming in general. The main goal of this project is to develop a graphical user interface that allows to, intuitively, represent constraint satisfaction problems. The idea is to visually represent the variables of the problem, their domains and the problem constraints and enable the user to interact with an adequate constraint solver to process the constraints and compute the solutions. Moreover, the graphical interface should be capable of configure the solver’s parameters and present solutions in an appealing interactive way. As a proof of concept, the developed application – GraphicalConstraints – focus on continuous constraint programming, which deals with real valued variables and numerical constraints (equations and inequalities). RealPaver, a state-of-the-art solver in continuous domains, was used in the application. The graphical interface supports all stages of constraint processing, from the design of the constraint network to the presentation of the end feasible space solutions as 2D or 3D boxes.

Predictor-Corrector Primal-Dual Interior Point Method for Solving Economic Dispatch Problems: A Postoptimization Analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A branch-and-price approach to p-median location problems

This paper describes a branch-and-price algorithm for the p-median location problem. The objective is to locate p facilities (medians) such as the sum of the distances from each demand point to its nearest facility is minimized. The traditional column generation process is compared with a stabilized approach that combines the column generation and Lagrangean/surrogate relaxation. The Lagrangean/surrogate multiplier modifies; the reduced cost criterion, providing the selection of new productive columns at the search tree. Computational experiments are conducted considering especially difficult instances to the traditional column generation and also with some large-scale instances. (C) 2004 Elsevier Ltd. All rights reserved.

A Beam Search Method to Solve the Problem of Assignment Cells to Switches in a Cellular Mobile Network

Assigning cells to switches in a cellular mobile network is known as an NP-hard optimization problem. This means that the alternative for the solution of this type of problem is the use of heuristic methods, because they allow the discovery of a good solution in a very satisfactory computational time. This paper proposes a Beam Search method to solve the problem of assignment cell in cellular mobile networks. Some modifications in this algorithm are also presented, which allows its parallel application. Computational results obtained from several tests confirm the effectiveness of this approach and provide good solutions for large scale problems.

Efficient robust optimization based on polynomial chaos and tabu search algorithm

The study of robust design methodologies and techniques has become a new topical area in design optimizations in nearly all engineering and applied science disciplines in the last 10 years due to inevitable and unavoidable imprecision or uncertainty which is existed in real word design problems. To develop a fast optimizer for robust designs, a methodology based on polynomial chaos and tabu search algorithm is proposed. In the methodology, the polynomial chaos is employed as a stochastic response surface model of the objective function to efficiently evaluate the robust performance parameter while a mechanism to assign expected fitness only to promising solutions is introduced in tabu search algorithm to minimize the requirement for determining robust metrics of intermediate solutions. The proposed methodology is applied to the robust design of a practical inverse problem with satisfactory results.

Tabu search algorithm for network synthesis

Large scale combinatorial problems such as the network expansion problem present an amazingly high number of alternative configurations with practically the same investment, but with substantially different structures (configurations obtained with different sets of circuit/transformer additions). The proposed parallel tabu search algorithm has shown to be effective in exploring this type of optimization landscape. The algorithm is a third generation tabu search procedure with several advanced features. This is the most comprehensive combinatorial optimization technique available for treating difficult problems such as the transmission expansion planning. The method includes features of a variety of other approaches such as heuristic search, simulated annealing and genetic algorithms. In all test cases studied there are new generation, load sites which can be connected to an existing main network: such connections may require more than one line, transformer addition, which makes the problem harder in the sense that more combinations have to be considered.

A modified ant colony optimization algorithm modeled on tabu-search methods

An earlier model underlying the foraging strategy of a pachycodyla apicalis ant is modified. The proposed algorithm incorporates key features of the tabu-search method in the development of a relatively simple but robust global ant colony optimization algorithm. Numerical results are reported to validate and demonstrate the feasibility and effectiveness of the proposed algorithm in solving electromagnetic (EM) design problems.

A Lagrangian bound for many-to-many assignment problems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)