Solving bi-objective flow shop problem with hybrid path relinking algorithm

This paper presents and investigates different ways to integrate path relinking techniques into the hypervolume-based multi-objective local search algorithm (HBMOLS). We aim to evaluate the effectiveness of different path relinking strategies, these strategies focus on two main steps: the ways of path generation and the mechanisms of solutions selection. We propose different methods to establish the path relinking algorithms in a multi-objective context. Computational results on a bi-objective flow shop problem (FSP) and a statistical comparison are reported in the paper. In comparison with two versions of HBMOLS, the algorithms selecting a set of solutions located in the middle of the generated path are efficient. The behavior of these algorithms sheds light on ways to further improvement

Hypervolume-based multi-objective local search

This paper presents a multi-objective local search, where the selection is realized according to the hypervolume contribution of solutions. The HBMOLS algorithm proposed is inspired from the IBEA algorithm, an indicator-based multi-objective evolutionary algorithm proposed by Zitzler and Künzli in 2004, where the optimization goal is defined in terms of a binary indicator defining the selection operator. In this paper, we use the indicator optimization principle, and we apply it to an iterated local search algorithm, using hypervolume contribution indicator as selection mechanism. The methodology proposed here has been defined in order to be easily adaptable and to be as parameter-independent as possible. We carry out a range of experiments on the multi-objective flow shop problem and the multi-objective quadratic assignment problem, using the hypervolume contribution selection as well as two different binary indicators which were initially proposed in the IBEA algorithm. Experimental results indicate that the HBMOLS algorithm is highly effective in comparison with the algorithms based on binary indicators

Ground instability detection using PS-InSAR in Lanzhou, China

This paper reports on the application of radar satellite data and Persistent Scatterer Interferometry (PS-InSAR) techniques for the detection of ground deformation in the semi-arid loess region of Lanzhou, northwestern China. Compared with Synthetic Aperture Radar Interferometry (InSAR), PS-InSAR overcomes the problems of temporal and geometric de-correlation and atmospheric heterogeneities by identifying persistent radar targets (PS) in a series of interferograms. The SPINUA algorithm was used to process 40 ENVISAT ASAR images for the study period 2003–2010. The analysis resulted in the identification of over 140000 PS in the greater Lanzhou area covering some 300 km2. The spatial distribution of moving radar targets was checked during a field campaign and highlights the range of ground instability problems that the Lanzhou area faces as urban expansion continues to accelerate. The PS-InSAR application detected ground deformations with rates up to 10 mm a−1; it resulted in the detection of previously unknown unstable slopes and two areas of subsidence. Lanzhou is the capital of Gansu Province and is one of the most important industrial cities in NW China (Fig. 1). The 12th Five-Year Plan and the 2011 National Economic and Social Development Statistical Bulletin of Lanzhou City indicate that the gross domestic product (GDP) of Lanzhou more than doubled in the last decade, reaching some 136 billion Yuan (c. £13.6 billion). This is associated with a rapid increase in the urban population and current forecasts suggest that the remaining undeveloped land can sustain further development for only some 10–15 years (Yao 2008). Increasingly, people have to encroach on marginal areas having a greater potential for ground instability. Since 1949, a variety of geohazards (mainly comprising landslides, debris flows, soil collapse, subsidence and floods) in Lanzhou have caused some 676 deaths and an estimated cumulative direct economic loss of some 756 million Yuan (Ding & Li 2009; Dijkstra et al. 2014). It is expected that further casualties and economic impacts will result in this unstable landscape unless a better understanding of the spatial distribution and causes of typical geohazards involving ground instability can be implemented in the development of land-use management practices, urban planning and the design of mitigation strategies. Satellite-based radar interferometry provides an opportunity to map ground deformation over large areas of interest. This paper highlights the use of PS-InSAR (Permanent Scatterer Synthetic Aperture Radar Interferometry) in a region where an incomplete ground instability inventory exist

Forecasting the magnitude of potential landslides based on InSAR techniques

A new method, combining empirical modeling with time series Interferometric Synthetic Aperture Radar (InSAR) data, is proposed to provide an assessment of potential landslide volume and area. The method was developed to evaluate potential landslides in the Heitai river terrace of the Yellow River in central Gansu Province, China. The elevated terrace has a substantial loess cover and along the terrace edges many landslides have been triggered by gradually rising groundwater levels following continuous irrigation since 1968. These landslides can have significant impact on communities, affecting lives and livelihoods. Developing effective landslide risk management requires better understanding of potential landslide magnitude. Fifty mapped landslides were used to construct an empirical power-law relationship linking landslide area (AL) to volume (VL) (VL = 0.333 × AL1.399). InSAR-derived ground displacement ranges from −64 mm/y to 24 mm/y along line of sight (LOS). Further interpretation of patterns based on remote sensing (InSAR & optical image) and field survey enabled the identification of an additional 54 potential landslides (1.9 × 102 m2 ≤ AL ≤ 8.1 × 104 m2). In turn this enabled construction of a map that shows the magnitude of potential landslide activity. This research provides significant further scientific insights to inform landslide hazard and risk management, in a context of ongoing landscape evolution. It also provides further evidence that this methodology can be used to quantify the magnitude of potential landslides and thus contribute essential information towards landslide risk management

Dynamic Yield Strength and Spall Strength of Alumina Short Fiber Reinforced ZL109 Cast Aluminium Alloy

This paper describes the results of plate impact experiments conducted on a alumina short fiber reinforced ZL109 cast aluminium alloy. The loading was produced by a 100mm bore light gas gun. The metal-matrix composite specimen was backed with a PMMA. Manganin gauges were used to measure the normal stress history at the interface between the specimen and the PMMA. The dynamic yield strength and spall strength of the metal-matrix composite were determined