A Cross-National Comparison E-government Success Measures: A Theory-Based Empirical Research

The continuing rapid convergence of government and e-technologies presents new opportunities for research to investigate the ways citizens interact with e-government. The literature in the area is, however, still in its infancy with little or no theoretically grounded empirical research conducted in the area. The present research investigates citizen experience with e-government in the United States and Spain by utilizing difference tests. Results of the difference tests show that the Spanish e-government citizens put more emphasis on information quality in terms of relevance, reliability, timeliness, clarity, conciseness, and currency. Results of the difference tests also show that for the system usage construct, e-government citizens on both side of the Atlantic agree that their e-government should provide superior user training, facilitate use of extranets to communicate with governmental agencies, allow automated transmitting and processing of data, and allow real time monitoring of citizen request for information in an e-government integrated with governmental agencies environment

MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework

International audienceAutomated algorithm configuration procedures play an increasingly important role in the development and application of algorithms for a wide range of computationally challenging problems. Until very recently, these configuration procedures were limited to optimising a single performance objective, such as the running time or solution quality achieved by the algorithm being configured. However, in many applications there is more than one performance objective of interest. This gives rise to the multi-objective automatic algorithm configuration problem, which involves finding a Pareto set of configurations of a given target algorithm that characterises trade-offs between multiple performance objectives. In this work, we introduce MO-ParamILS, a multi-objective extension of the state-of-the-art single-objective algorithm configuration framework ParamILS, and demonstrate that it produces good results on several challenging bi-objective algorithm configuration scenarios compared to a base-line obtained from using a state-of-the-art single-objective algorithm configurator

Tuning Tabu Search strategies via visual diagnosis

Abstract: While designing working metaheuristics can be straightforward, tuning them to solve the underlying combinatorial optimization problem well can be tricky. Several tuning methods have been proposed but they do not address the new aspect of our proposed classification of the metaheuristic tuning problem: tuning search strategies. We propose a tuning methodology based on Visual Diagnosis and a generic tool called Visualizer for Metaheuristics Development Framework (V-MDF) to address specifically the problem of tuning search (particularly Tabu Search) strategies. Under V-MDF, we propose the use of a Distance Radar visualizer where the human and computer can collaborate to diagnose the occurrence of negative incidents along the search trajectory on a set of training instances, and to perform remedial actions on the fly. Through capturing and observing the outcomes of actions in a Rule-Base, the user can then decide how to tune the search strategy effectively for subsequent use

Supply network science: Emergence of a new perspective on a classical field.

Supply networks emerge as companies procure goods from one another to produce their own products. Due to a chronic lack of data, studies on these emergent structures have long focussed on local neighbourhoods, assuming simple, chain-like structures. However, studies conducted since 2001 have shown that supply chains are indeed complex networks that exhibit similar organisational patterns to other network types. In this paper, we present a critical review of theoretical and model based studies which conceptualise supply chains from a network science perspective, showing that empirical data do not always support theoretical models that were developed, and argue that different industrial settings may present different characteristics. Consequently, a need that arises is the development and reconciliation of interpretation across different supply network layers such as contractual relations, material flow, financial links, and co-patenting, as these different projections tend to remain in disciplinary siloes. Other gaps include a lack of null models that show whether the observed properties are meaningful, a lack of dynamical models that can inform how layers evolve and adopt to changes, and a lack of studies that investigate how local decisions enable emergent outcomes. We conclude by asking the network science community to help bridge these gaps by engaging with this important area of research

Designing and comparing multiple portfolios of parameter configurations for online algorithm selection

National Research Foundation (NRF) Singapore under its International Research Centres in Singapore Funding Initiativ

Increasing Sustainability of Logistic Networks by Reducing Product Losses: A Network DEA Approach

This paper considers a multiproduct supply network, in which losses (e.g., spoilage of perishable products) can occur at either the nodes or the arcs. Using observed data, a Network Data Envelopment Analysis (NDEA) approach is proposed to assess the efficiency of the product flows in varying periods. Losses occur in each process as the observed output flows are lower than the observed input flows. The proposed NDEA model computes, within the NDEA technology, input and output targets for each process. The target operating points correspond to the minimum losses attainable using the best observed practice. The efficiency scores are computed comparing the observed losses with the minimum feasible losses. In addition to computing relative efficiency scores, an overall loss factor for each product and each node and link can be determined, both for the observed data and for the computed targets. A detailed illustration and an experimental design are used to study and validate the proposed approach. The results indicate that the proposed approach can identify and remove the inefficiencies in the observed data and that the potential spoilage reduction increases with the variability in the losses observed in the different periods

A simple search heuristic for the MCLP: Application to the location of ambulance bases in a rural region

In the location of ambulance bases for medical assistance, an adequate time of response must be guaranteed for each area in the region covered, incurring the minimum operating costs. Several linear models (such as the maximal covering location problem, MCLP) have been developed for designing these emergency systems which guarantee a certain cover whilst minimising determined costs. The computational difficulty involved in resolving large scale problems occasionally means trying to offer solutions using metaheuristics. This article presents the solution to the problem of locating ambulance bases in the province of Leøn (Spain), using the tabu search metaheuristic, which in its simplest version already offers good results, and which makes it a tool to be kept very much in mind when a rapid solution is needed to such problems.location ambulance service emergency medical service location tabu search