A dynamic multiarmed bandit-gene expression programming hyper-heuristic for combinatorial optimization problems

Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework has two levels, namely, the high level strategy (heuristic selection mechanism and the acceptance criterion) and low level heuristics (a set of problem specific heuristics). Due to the different landscape structures of different problem instances, the high level strategy plays an important role in the design of a hyper-heuristic framework. In this paper, we propose a new high level strategy for a hyper-heuristic framework. The proposed high-level strategy utilizes a dynamic multiarmed bandit-extreme value-based reward as an online heuristic selection mechanism to select the appropriate heuristic to be applied at each iteration. In addition, we propose a gene expression programming framework to automatically generate the acceptance criterion for each problem instance, instead of using human-designed criteria. Two well-known, and very different, combinatorial optimization problems, one static (exam timetabling) and one dynamic (dynamic vehicle routing) are used to demonstrate the generality of the proposed framework. Compared with state-of-the-art hyper-heuristics and other bespoke methods, empirical results demonstrate that the proposed framework is able to generalize well across both domains. We obtain competitive, if not better results, when compared to the best known results obtained from other methods that have been presented in the scientific literature. We also compare our approach against the recently released hyper-heuristic competition test suite. We again demonstrate the generality of our approach when we compare against other methods that have utilized the same six benchmark datasets from this test suite

myBas driving cycle for Kuala Terengganu city

Driving cycles are series of data points that represent vehicle speed versus time sequenced profile developed for specific road, route, city or certain location. It is widely utilized in the application of vehicle manufacturers, environmentalists and traffic engineers. Since the vehicles are one of the higher air pollution sources, driving cycle is needed to evaluate the fuel consumption and exhaust emissions. The main objectives in this study are to develop and characterize the driving cycle for myBAS in Kuala Terengganu city using established k-means clustering method and to analyse the fuel consumption and emissions using advanced vehicle simulator (ADVISOR). Operation of myBAS offers 7 trunk routes and one feeder route. The research covered on two operation routes of myBAS which is Kuala Terengganu city-feeder and from Kuala Terengganu to Jeti Merang where the speed-time data is collected using on-board measurement method. In general, driving cycle is made up of a few micro-trips, defined as the trip made between two idling periods. These micro-trips cluster by using the k-means clustering method and matrix laboratory software (MATLAB) is used in developing myBAS driving cycle. Typically, developing the driving cycle based on the real-world in resulting improved the fuel economy and emissions of myBAS

Characterization of Activated Carbons from Oil-Palm Shell by CO 2

Activated carbons can be produced from different precursors, including coals of different ranks, and lignocellulosic materials, by physical or chemical activation processes. The objective of this paper is to characterize oil-palm shells, as a biomass byproduct from palm-oil mills which were converted into activated carbons by nitrogen pyrolysis followed by CO2 activation. The effects of no holding peak pyrolysis temperature on the physical characteristics of the activated carbons are studied. The BET surface area of the activated carbon is investigated using N2 adsorption at 77 K with selected temperatures of 500, 600, and 700°C. These pyrolysis conditions for preparing the activated carbons are found to yield higher BET surface area at a pyrolysis temperature of 700°C compared to selected commercial activated carbon. The activated carbons thus result in well-developed porosities and predominantly microporosities. By using this activation method, significant improvement can be obtained in the surface characteristics of the activated carbons. Thus this study shows that the preparation time can be shortened while better results of activated carbon can be produced

Reaction optimization of Aspergillus niger α-L-arabinofuranosidase for improved arabinose production from kenaf stem

There are abundant of lignocellulosic biomass readily available with varying compositions. Kenaf (Hibiscus cannabinus) is one of this lignocellulosic biomass that has a high content of hemicellulose. This particular hemicellulose is composed of high arabinoxylan, which is a xylan backbone with arabinofuranosyl branches. In order to hydrolyze arabinoxylan, a branching enzyme is needed. Therefore, α-L-arabinofuranosidase from Aspergillus niger ATCC120120 (AnabfA) was used to hydrolyzed pre-treated kenaf and the reaction conditions were optimized using central composite design (CCD) to produce a significant amount of arabinose. There were 20 experiments conducted with 1.68 star points and 6 replicates at the centre points. The reaction conditions that were optimized are enzyme loading, substrate concentration and reaction time in which resulted with 88 U AnabfA activity, 0.9% (w/v) and 48 h, respectively. These optimized conditions managed to increase the yield of arabinose with 47.17 mg/g arabinose produced

A harmony search algorithm for nurse rostering problems

Harmony search algorithm (HSA) is a relatively new nature-inspired algorithm. It evolves solutions in the problem search space by mimicking the musical improvisation process in seeking agreeable harmony measured by aesthetic standards. The nurse rostering problem (NRP) is a well-known NP-hard scheduling problem that aims at allocating the required workload to the available staff nurses at healthcare organizations to meet the operational requirements and a range of preferences. This work investigates research issues of the parameter settings in HSA and application of HSA to effectively solve complex NRPs. Due to the well-known fact that most NRPs algorithms are highly problem (or even instance) dependent, the performance of our proposed HSA is evaluated on two sets of very different nurse rostering problems. The first set represents a real world dataset obtained from a large hospital in Malaysia. Experimental results show that our proposed HSA produces better quality rosters for all considered instances than a genetic algorithm (implemented herein). The second is a set of well-known benchmark NRPs which are widely used by researchers in the literature. The proposed HSA obtains good results (and new lower bound for a few instances) when compared to the current state of the art of meta-heuristic algorithms in recent literature

Exploring institutional reform of Korean civil service pension: advocacy coalition framework, policy knowledge and social innovation

Abstract This paper examines what factors are associated with the 2015 pension reform of Korean civil servant as social innovation. We explore what lessons we can learn from the pension reform in terms of the Advocacy Coalition Framework (ACF) model. The ACF model allows us to identify how the substantial reform is, relying on policy knowledge and entrepreneurs, possible in terms of political and social consensus. It also clearly demonstrates the possibility of systematic pension reform at an appropriate level through social learning and policy learning. Through the ACF model, we review how South Koreas civil servant pension reform act occurred at the end of May 2015. The temporal scope covers from 2009 latest reform, and the 2014s President administrative policy speech that had strongly been showed her will to reform the pension issue to the end of May 2015 when the reform bill enacted. We investigate each advocacy coalition in order to elucidate the actors that constitute the two coalition groups and to scrutinize whether a policy broker had existed in the process. We also attempt to find the relatively stable parameters and external events that affected the reform and also the belief system that shared by two advocacy coalition group. The result clearly shows that the two coalition groups shared their normative beliefs ultimately, for example, the need to change the current civil servants pension system, but, the gap in the numerical change in the policy core belief and secondary belief between the two actors had seemed to be excessively large and uncompromising. A policy broker who can coordinate the interests and interests of stakeholder groups over the government pension reform proposal was desperately needed. Negotiation and leadership of the policy entrepreneurs led to a settlement of the government pension reform proposal at the end of May 2015. Their entrepreneurial activities led to an appropriate level of social consensus on the sustainable reform of pension system through policy knowledge and learning. Further research is required to explore how models of socially innovative forms of governance are created in various pension reforms across various countries. It is also required to examine how policy entrepreneurs use policy knowledge and information for a successful institutional reform through social innovation across various countries

Buckling and post-buckling improvements of laminated composite plates using finite element method

The improvements of buckling and post-buckling behaviours of laminated composite plates were done by changing the composite related parameters such as the level of anisotropy, thickness to width ratio and boundary condition. In recent years, shape memory alloy has been used to achieve such improvements. A study is conducted on the buckling and post-buckling improvements of composite plates due to the combined effects of composite and shape memory alloy related parameters. Shape memory alloy wires are embedded within laminated composite plates and the amount of recovery stress induced by the shape memory wires is predicted using the Brinson’s model. A geometric non-linear finite element method is used to model the buckling and post-buckling behaviours of shape memory alloy composite plates and source codes are developed to solve the model. It is found that significant improvements in buckling and post-buckling behaviours of composite plates can be attained by combining the effect of shape memory alloy and composite related parameters