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Spatial optimization problems, such as route selection, usually involve multiple, conflicting objectives relevant to locations. An ideal approach to solving such multiobjective optimization problems (MOPs) is to find an evenly distributed set of Pareto-optimal alternatives, which is capable of representing the possible trade-off among different objectives. However, these MOPs are commonly solved by combining the multiple objectives into a parametric scalar objective, in the form of a weighted sum function. It has been found that this method fails to produce a set of well spread solutions by disregarding the concave part of the Pareto front. In order to overcome this ill-behaved nature, a novel adaptive approach has been proposed in this paper. This approach seeks to provide an unbiased approximation of the Pareto front by tuning the search direction in the objective space according to the largest unexplored region until a set of well-distributed solutions is reached. To validate the proposed methodology, a case study on multiobjective routing has been performed using the Singapore road network with the support of GIS. The experimental results confirm the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

As security is of concern today, there is an urgent need to review and improve the way trucks carrying hazardous materials (HAZMATs) are being routed. Routing of such vehicles should not only ensure the safety of travelers in the network, but should also consider the risk of the HAZMAT being used as weapon of mass destruction. This paper seeks to identify evaluation factors used to route these vehicles, taking into consideration safety, costs and most importantly, security. A Geographic Information System (GIS) is used to quantify the factors on each link in the network that contribute to each of the evaluation criteria for a possible route. The Analytic Hierarchy Process (AHP) is used to assign weights to the factors, depending on their perceived relative importance. Each route can then be quantified by a cost function and the suitability of the routes for HAZMAT transportation can be compared. The proposed route evaluation method is demonstrated on a portion of road network in Singapore. [ABSTRACT FROM AUTHOR]

The complete nucleotide sequences of RNA1 and RNA2 from greasy grouper (Epinephelus tauvina) nervous necrosis virus (GGNNV), Singapore strain, were determined. 5' RACE and RNA ligation were used to obtain the complete nucleotide sequences of the 5' and 3' non-coding regions (NCRs). GGNNV RNA1 was determined to be 3103 nt long, containing an ORF of 982 aa, while GGNNV RNA2 was determined to be 1433 nt long, containing an ORF of 338 aa. Both GGNNV RNAs are longer than those of other published betanodavirus sequences and the additional nucleotides were located within the NCRs. Analysis of GGNNV RNA2 revealed that it is closely related to red-spotted grouper nervous necrosis virus and that both grouper viruses share the same neutralization epitope. Predicted domains for six RNA-dependent RNA polymerase motifs and two putative ORFs (proteins B1 and B2) were confirmed by sequence analysis of GGNNV RNA1.