Multiobjective optimization for interwoven systems

An effective genetic algorithm approach to multiobjective resource allocation problems (MORAPs)

A multi-population genetic algorithm to solve multi-objective scheduling problems for parallel machines

Ecosystem coupling: A unifying framework to understand the functioning and recovery of ecosystems

Purpose This paper aims to estimate a New Keynesian small open economy dynamic stochastic general equilibrium (DSGE) model for Egypt using Bayesian techniques and data for the period FY2004/2005:Q1-FY2015/2016:Q4 to assess monetary and fiscal policy interactions and their impact on economic stabilization. Outcomes of monetary and fiscal authority commitment to policy instruments, interest rate, government spending and taxes, are evaluated using Taylor-type and optimal simple rules. Design/methodology/approach The study extends the stylized micro-founded small open economy New Keynesian DSGE model, proposed by Lubik and Schorfheide (2007), by explicitly introducing fiscal policy behavior into the model (Fragetta and Kirsanova, 2010 and Çebi, 2011). The model is calibrated using quarterly data for Egypt on key macroeconomic variables during FY2004/2005:Q1-FY2015/2016:Q4; and Bayesian methods are used in estimation. Findings The results show that monetary and fiscal policy instruments in Egypt contribute to economic stability through their effects on inflation, output and debt stock. The monetary policy Taylor rule estimates reveal that the Central Bank of Egypt (CBE) attaches significant importance to anti-inflationary policy and (to a lesser extent) to output targeting but responds weakly to nominal exchange rate variations. CBE decisions are significantly influenced by interest rate smoothing. Egyptian fiscal policy has an important role in output and government debt stabilization. Additionally, the fiscal authority chooses pro-cyclical government spending and counter-cyclical tax policies for output stabilization. Again, past values of the fiscal instruments are influential in the evolution of the future fiscal policy-making process. Originality/value A few studies have examined the interaction between monetary and fiscal policy in Egypt within a unified framework. The presented paper integrates the monetary and fiscal policy analysis within a unified dynamic general equilibrium open economy rational expectations framework. Without such a framework, it would not be easy to jointly analyze monetary and fiscal transmission mechanisms for output, inflation and debt. Also, it would be neither possible to contrast the outcome of monetary and fiscal authorities commitment to a simple Taylor instrument rule vis-à-vis optimal policy outcomes nor to assess the behavior of monetary and fiscal agents in macroeconomic stability in context of an active/passive policy decisions framework.

The behavior of distributed shared memory systems is dictated by the memory consistency model. Several memory consistency models have been proposed in the literature and they fit basically in two categories: uniform and hybrid models. To provide a better understanding of the semantics of the memory models, researchers have proposed formalisms to define them. Unfortunately, most of the work has been done in the definition of uniform memory models. We propose a general, unified and formal framework where uniform and hybrid memory consistency models can be defined. To prove the generality of the framework, we use it to define the following memory models: atomic consistency, sequential consistency, causal consistency, PRAM consistency, slow memory, weak ordering, release consistency, entry consistency and scope consistency.

4 - Evolution Strategies-Based Metaheuristics in Structural Design Optimization

This paper studies a traffic grooming in wavelength-division multiplexing (WDM) mesh networks for the SONET/SDH streams requested between node pairs. The traffic could be groomed at the access node before converting to an optical signal carried in the all-optical network. We design a virtual topology with a given physical topology to satisfy multiple objectives and constraints. The grooming problem of a static demand is considered as an optimization problem. The algorithms found in the literatures focus on a single objective either to maximize the performance or to minimize the cost. We propose a multiobjective evolutionary algorithm to solve a grooming problem that optimizes multiple objectives all together at the same time. In this paper we consider the optimization of three objectives: maximize the traffic throughput, minimize the number of transceivers, and minimize the average propagation delay or average hop counts. The simulation results show that our approach is superior to an existing heuristic approaches for the 6-node benchmark network in an acceptable running time.

This paper proposes a new multi-objective optimization algorithm inspired by the Newtonian Law of Gravity. The new algorithm is a multiple objective extension of the single objective optimization Gravitational Search Algorithm. Generally, we know various multi-objective algorithms with leader selection schemes. The Leader guides the population towards Pareto fronts. As a result, the algorithm becomes complex in nature. To reduce that part of the cost, we introduce a new algorithm which does not use the leader for guidance but relies on its own population to obtain the non-dominated set of solutions. The algorithm has been tested on several benchmark functions and has produced a good number of solutions. Our purpose of research is to showcase that the memory-less property of the single objective Gravitational Search Algorithm can be used to solve multiple objective problems.

Emergency response system is a complex system of systems (SoS). The introduction of connected and autonomous vehicles (CAVs) introduces an extra dimension into the complexity. Future emergency response must be able to take into account of the autonomous vehicles with different automation levels and leverage the increasing connectivity and automation for efficient emergency response. Architecture frameworks have long been used for system engineering for large complex systems. The emerging unified architecture framework converges previous architecture frameworks for a unified one towards both military and civilian use. Based on the scenario of emergency response with CAVs on highways, this paper motivates an enterprise architecture for emergency response system of systems (ERSoS) with identification of the key challenges and opportunities in addition to a proposal of required capabilities. The work is a first iteration of an enterprise architecture for ERSoS with CAVs and forms part of the overall ERSoS architecture development process.

Plasmonic nanoparticles are widely exploited in diverse bioapplications ranging from therapeutics to biosensing and biocomputing because of their strong and tunable light-matter interactions, facile and versatile chemical/biological ligand modifications, and biocompatibility. With the rapid growth of nanobiotechnology, understanding dynamic interactions between nanoparticles and biological systems at the molecular or single-particle level is becoming increasingly important for interrogating biological systems with functional nanostructures and for developing nanoparticle-based biosensors and therapeutic agents. Therefore, significant efforts have been devoted to precisely design and create nano-bio interfaces by manipulating the nanoparticles' size, shape, and surface ligand interactions with complex biological systems to maximize their performance and avoid unwanted responses, such as their agglomeration and cytotoxicity. However, investigating physicochemical interactions at the nano-bio interfaces in a quantitative and controllable manner remains challenging, as the interfaces involve highly complex networks between nanoparticles, biomolecules, and cells across multiple scales, each with a myriad of different chemical and biological interactions. A lipid bilayer is a membrane made of two layers of lipid molecules that forms a barrier around cells and plays structural and functional roles in diverse biological processes because they incorporate and present functional molecules (such as membrane proteins) with lateral fluidity. Plasmonic nanoparticles conjugated on lipid membranes provide reliable analytical labels and functional moieties that allow for studying and manipulating interactions between nanoparticles and molecules with single-particle resolution; they also serve as efficient tools for applying optical, mechanical, and thermal stimuli to biological systems, which stem from plasmonic properties. Recently, new opportunities have emerged by interfacing nanoparticle-modified lipid bilayers (NLBs) with complex systems such as molecular circuits and living systems. In this Account, we briefly review how plasmonic properties can be beneficially harnessed on lipid bilayer membranes to investigate the structures and functions of cellular membranes and to develop new platforms for biomedical applications. In particular, we discuss the versatility of supported lipid bilayers (SLBs), which are planar lipid bilayers on hydrophilic substrates, as dynamic biomaterials that provide lateral fluidity and cell membrane-like environments. We then summarize our efforts to create a quantitative analytical platform utilizing nanoparticles as active building blocks and SLBs as integrative substrates. Through this bottom-up approach, various functionalized nanoparticles have been introduced onto lipid bilayers to render nanoparticle-nanoparticle, nanoparticle-lipid bilayer, and biomolecule-lipid bilayer interfaces programmable. Our system provides a new class of tools for studying thermodynamics and kinetics in complex networks of nanostructures and for realizing unique applications in biosensing and biocomputing.

Modern research in optical physics has achieved quantum control of strong interactions between a single atom and one photon within the setting of cavity quantum electrodynamics (cQED). However, to move beyond current proof-of-principle experiments involving one or two conventional optical cavities to more complex scalable systems that employ N >> 1 microscopic resonators requires the localization of individual atoms on distance scales < 100 nm from a resonator's surface. In this regime an atom can be strongly coupled to a single intracavity photon while at the same time experiencing significant radiative interactions with the dielectric boundaries of the resonator. Here, we report an initial step into this new regime of cQED by way of real-time detection and high-bandwidth feedback to select and monitor single Cesium atoms localized ~100 nm from the surface of a micro-toroidal optical resonator. We employ strong radiative interactions of atom and cavity field to probe atomic motion through the evanescent field of the resonator. Direct temporal and spectral measurements reveal both the significant role of Casimir-Polder attraction and the manifestly quantum nature of the atom-cavity dynamics. Our work sets the stage for trapping atoms near micro- and nano-scopic optical resonators for applications in quantum information science, including the creation of scalable quantum networks composed of many atom-cavity systems that coherently interact via coherent exchanges of single photons.

This paper offers a new approach to integration of modules in an intelligent sensor system. Such a system requires that a set of modules-each doing a smaller portion of the overall task-be integrated within a unifying framework. From the perspective of computational systems, this problem holds a considerable interest because it is characterized by a set of coexisting mathematical objectives that need to be optimized simultaneously. In this sense, the design considerations necessitate the introduction of problem solving with multiple objectives. This paper explores these issues in the instance when each module is associated with a mathematical objective that is a function of the outputs of other modules. The integration problem is formulated and what is required of a good solution is presented. This examination interprets the decentralized mediation of conflicting subgoals as promoting a N-player game amongst the modules to be integrated and proposes a game-theoretic integration framework. We model the interaction among the modules as a noncooperative game and argue that this strategy leads to a framework in which the solutions correspond to a compromise decision. The application of this framework in image analysis motivates the hope that a framework such as game-theoretic integration will facilitate the development of general design principles for "modular" systems.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

In the current social, physical, economical and environmental circumstances of scarcity, the design and management of vital lifelines like transportation systems, especially within the metropolitan context, are subject to the implementation of multiple objectives in a unified framework. Thus, one of the most important issues is the identification of optimal trade-offs among crucial objectives both from the designer's as well as from the users' perspective. In the current study a comprehensive framework for estimating optimal interrelations and dilemmas among emissions-related carbon footprint and other (social- and economic-related) features of urban road networks design and operation are presented and analyzed, based on techniques of multi-objective and hierarchical mathematical programming with equilibrium constraints, solved by suitable hybridization of evolutionary algorithms. The results of the proposed optimization methodological approach provide the Pareto Frontier of solutions, which corresponds to optimal trade-offs amongst multiple objectives. The computational experience from the application of the proposed methodological approach on a part of a realistic urban network is presented, providing evidence on the applicability as well as on the computational burden of such transportation design paradigms, but most importantly, on the dilemmas emerging in sustainable design and planning of transportation systems.

In this book chapter, we propose a fully automated approach for tracking of multiple objects across multiple cameras with overlapping and non-overlapping views in a unified framework without initial training or prior camera calibration. For tracking with a single camera, Kalman filter and adaptive particle-sampling techniques are integrated for multiple objects tracking. When extended to tracking over multiple cameras, the relations between adjacent cameras are learned systematically by using image registration techniques for consistent handoff of tracking-object labels across cameras. In addition, object appearance measurement is employed to validate the labeling results. Experimental results demonstrate the performance of our approach on real video sequences for cameras with overlapping and non-overlapping views.

Process and energy models provide an invaluable tool for design, analysis and optimisation. These models are usually based upon a number of assumptions, simplifications and approximations, thereby introducing uncertainty in the model predictions. Making model based optimal decisions under uncertainty is therefore a challenging task. This issue is further exacerbated when more than one objective is to be optimised simultaneously, resulting in a Multi-Objective Optimisation (MO2) problem. Even though, some methods have been proposed for MO2 problems under uncertainty, two separate optimisation techniques are employed; one to address the multi-objective aspect and another to take into account uncertainty. In the present work, we propose a unified optimisation framework for linear MO2 problems, in which the uncertainty and the multiple objectives are modelled as varying parameters. The MO2 under uncertainty problem (MO2U2) is thus reformulated and solved as a multi-parametric programming problem. The solution of the multi-parametric programming problem provides the optimal solution as a set of parametric profiles.