This chapter presents the application of a comprehensive statistical analysis for both algorithmic performance comparison and optimal parameter estimation on a multi-objective digital signal processing problem. The problem of designing optimum digital finite impulse response (FIR) filters with the simultaneous approximation of the filter magnitude and phase is posed as a multiobjective optimiza...

one main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. this paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between each pair of hubs. indeed, the nature of products is considered different and hub capacity constraint is also applied. due to ...

This paper addresses the stable scheduling of multi-objective problem in flexible job shop scheduling with random machine breakdown. Recently, numerous studies are conducted about robust scheduling; however, implementing a scheme which prevents a tremendous change between scheduling and after machine breakdown (preschedule and realized schedule, respectively) can be critical for utilizing avail...

Abstract We present an extension of SonOpt, the first ever openly available tool for sonification bi-objective population-based optimisation algorithms. SonOpt has already introduced benefits on understanding algorithmic behaviour by proposing use sound as a medium process monitoring The edition utilised two different paths to provide information convergence, population diversity, recurrence ob...

NSGA methodology discussed in Section 3.1 suffers from three weaknesses: computational complexity, non-elitist approach and the need to specify a sharing parameter. An improved version of NSGA known as NSGA-II, which resolved the above problems and uses elitism to create a diverse Pareto-optimal front, has been subsequently presented (Deb et al 2002). The main features of NSGA-II are low comput...

The water allocation problem is complex and requires a combination of regulations, policies, mechanisms to support management minimize the risk shortage among competing users. This paper compiles application multi-criteria decision-making (MCDM) related allocation. In this regard, aims identify discern pattern, distribution study regions, classifications, decision techniques for specific proble...

A new evolutionary multi-objective crowding algorithm (EMOCA) is evaluated using nine benchmark multiobjective optimization problems, and shown to produce non-dominated solutions with significant diversity, outperforming state-of-the-art multi-objective evolutionary algorithms viz., Non-dominated Sorting Genetic Algorithm – II (NSGA-II), Strength Pareto Evolutionary algorithm II (SPEA-II) and P...

Development of the Great Barrier Reef (GBR) catchments in the last 150 years has increased the loads of suspended sediment, nutrients and pesticides ('pollutants') delivered to the GBR. The scale and type of development, the pollutants generated and the ecosystems offshore vary regionally. We analysed the relative risk of pollutants from agricultural land uses and identified the sources of thes...

Nowadays, the citrus supply chain has been motivated by both industrial practitioners and researchers due to several real-world applications. This study considers a four-echelon citrus supply chain, consisting of gardeners, distribution centers, citrus storage, and fruit market. A Mixed Integer Non-Linear Programming (MINLP) model is formulated, which seeks to minimize the total cost and maximi...

In data mining, nugget discovery is the discovery of interesting classification rules that apply to a target class. In previous research, heuristic methods (Genetic algorithms, Simulated Annealing and Tabu Search) have been used to optimise a single measure of interest. This paper proposes the use of multiobjective optimisation evolutionary algorithms to allow the user to interactively select a...