A novel simulation-annealing enabled ranking and scaling statistical simulation constrained optimization algorithm for Internet-of-things (IoTs)

2020 ◽  
Vol 9 (4) ◽  
pp. 675-693 ◽  
Author(s):  
Adarsh Kumar ◽  
Saurabh Jain ◽  
Divakar Yadav
Keyword(s):  
Comparative Analysis ◽  
Tabu Search ◽  
Critical Infrastructure ◽  
Simulation Optimization ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Evolutionary Strategies ◽  
Small Scale ◽  
Content Type ◽  
Simplex Search

PurposeSimulation-based optimization is a decision-making tool for identifying an optimal design of a system. Here, optimal design means a smart system with sensing, computing and control capabilities with improved efficiency. As compared to testing the physical prototype, computer-based simulation provides much cheaper, faster and lesser time-and resource-consuming solutions. In this work, a comparative analysis of heuristic simulation optimization methods (genetic algorithms, evolutionary strategies, simulated annealing, tabu search and simplex search) is performed.Design/methodology/approachIn this work, a comparative analysis of heuristic simulation optimization methods (genertic algorithms, evolutionary strategies, simulated annealing, tabu search and simplex search) is performed. Further, a novel simulation annealing-based heuristic approach is proposed for critical infrastructure.FindingsA small scale network of 50–100 nodes shows that genetic simulation optimization with multi-criteria and multi-dimensional features performs better as compared to other simulation optimization approaches. Further, a minimum of 3.4 percent and maximum of 16.2 percent improvement is observed in faster route identification for small scale Internet-of-things (IoT) networks with simulation optimization constraints integrated model as compared to the traditional method.Originality/valueIn this work, simulation optimization techniques are applied for identifying optimized Quality of service (QoS) parameters for critical infrastructure which in turn helps in improving the network performance. In order to identify optimized parameters, Tabu search and ant-inspired heuristic optimization techniques are applied over QoS parameters. These optimized values are compared with every monitoring sensor point in the network. This comparative analysis helps in identifying underperforming and outperforming monitoring points. Further, QoS of these points can be improved by identifying their local optimum values which in turn increases the performance of overall network. In continuation, a simulation model of bus transport is taken for analysis. Bus transport system is a critical infrastructure for Dehradun. In this work, feasibility of electric recharging units alongside roads under different traffic conditions is checked using simulation. The simulation study is performed over five bus routes in a small scale IoT network.

scholarly journals Some applications of a novel desirability function in simultaneous optimization of multiple responses

2021 ◽  
Vol 49 (3) ◽  
pp. 534-548
Author(s):  
Velibor Marinković
Keyword(s):  
Comparative Analysis ◽  
Desirability Function ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
The Other ◽  
Simultaneous Optimization ◽  
Desirability Functions ◽  
Gradient Based ◽  
Response Optimization ◽  
Optimization Methodology

In the framework of multi-response optimization techniques, the optimization methodology based on the desirability function is one of the most popular and most frequently used methodologies by researchers and practitioners in engineering, chemistry, technology and many other fields of science and technique. Numerous desirability functions have been introduced to improve the performance of this optimization methodology. Recently, a novel desirability function for multi-response optimization is proposed, which is smooth, nonlinear, and differentiable, and thus more suitable for applying some of the more efficient gradient-based optimization methods. This paper evaluates the performance of the proposed method through six real examples. After a comparative analysis of the results, it is shown that the proposed method in a certain measure outperforms the other competitive optimization methods.

scholarly journals A review of conjunctive GW-SW management by simulation–optimization tools

2021 ◽  
Author(s):  
Shima Soleimani ◽  
Omid Bozorg-Haddad ◽  
Arezoo Boroomandnia ◽  
Hugo A. Loáiciga
Keyword(s):  
Water Resources ◽  
Water Resource Management ◽  
Simulation Optimization ◽  
Management Strategies ◽  
Optimization Methods ◽  
Conjunctive Use ◽  
Optimization Techniques ◽  
Hydrologic Models ◽  
Water Resources Systems ◽  
Simulation And Optimization

Abstract The conjunctive use of groundwater and surface water (GW-SW) resources has grown worldwide. Optimal conjunctive water use can be planned by coupling hydrologic models for the simulation of water systems with optimization techniques for improving management strategies. The coupling of simulation and optimization methods constitutes an effective approach to determine sustainable management strategies for the conjunctive use of these water resources; yet, there are challenges that must be addressed. This paper reviews (1) hydrologic models applied for the simulation of GW-SW interaction in the water resources systems, (2) conventional optimization methods, and (3) published works on optimized conjunctive GW-SW use by coupling simulation and optimization methods. This paper evaluates the pros and cons of GW-SW simulation tools and their applications, thus providing criteria for selecting simulation–optimization methods for GW-SW management. In addition, an assessment of GW-SW simulation–optimization tools applied in various studies over the world creates valuable knowledge for selecting suitable simulation–optimization tools in similar case studies for sustainable water resource management under multiple scenarios.

scholarly journals Optimization of Clustering in Wireless Sensor Networks: Techniques and Protocols

2021 ◽  
Vol 11 (23) ◽  
pp. 11448
Author(s):  
Ahmed Mahdi Jubair ◽  
Rosilah Hassan ◽  
Azana Hafizah Mohd Aman ◽  
Hasimi Sallehudin ◽  
Zeyad Ghaleb Al-Mekhlafi ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Optimization Methods ◽  
Base Station ◽  
Optimization Techniques ◽  
Wireless Sensor ◽  
Small Scale ◽  
Network Clustering ◽  
Head Node ◽  
Clustering Protocols ◽  
Clustering Optimization

Recently, Wireless Sensor Network (WSN) technology has emerged extensively. This began with the deployment of small-scale WSNs and progressed to that of larger-scale and Internet of Things-based WSNs, focusing more on energy conservation. Network clustering is one of the ways to improve the energy efficiency of WSNs. Network clustering is a process of partitioning nodes into several clusters before selecting some nodes, which are called the Cluster Heads (CHs). The role of the regular nodes in a clustered WSN is to sense the environment and transmit the sensed data to the selected head node; this CH gathers the data for onward forwarding to the Base Station. Advantages of clustering nodes in WSNs include high callability, reduced routing delay, and increased energy efficiency. This article presents a state-of-the-art review of the available optimization techniques, beginning with the fundamentals of clustering and followed by clustering process optimization, to classifying the existing clustering protocols in WSNs. The current clustering approaches are categorized into meta-heuristic, fuzzy logic, and hybrid based on the network organization and adopted clustering management techniques. To determine clustering protocols’ competency, we compared the features and parameters of the clustering and examined the objectives, benefits, and key features of various clustering optimization methods.

A Framework for Improving Logistics Operations at Container Terminals

2016 ◽  
pp. 1-23
Author(s):  
Julio Mar-Ortiz ◽  
Maria D. Gracia ◽  
Rosa G. González-Ramírez
Keyword(s):  
Research Agenda ◽  
Simulation Optimization ◽  
Optimization Methods ◽  
Optimal Number ◽  
Optimization Techniques ◽  
Container Terminals ◽  
Methodological Framework ◽  
Lean Logistics ◽  
Increase Productivity ◽  
Integrated Problems

Container terminals as strategic nodes in global supply chains require improving logistics operations in order to compete. This chapter addresses the problem of how to improve logistics operations to increase the container terminal's throughput and capacity by lean logistics principles and simulation optimization methods. Current research in container terminals is focused on solving specific decision problems at container terminals, e.g., determining the optimal number of equipment to increase productivity. However, there is little evidence of studies related to designing operations to increase performance indicators, such as truck turnaround times or crane productivity, through simulation-optimization models and lean logistics principles. Consequently, the aim of this chapter is to describe a methodological framework for improving logistics operations at container terminals using lean logistics principles and simulation-optimization techniques. A research agenda to explore the applicability and usefulness of the proposed approach on a set of integrated problems is finally proposed.

ON COMPARATIVE ANALYSIS OF PERFORMANCE OPTIMIZATION METHODS OF MULTI-PUMP UNITS

2020 ◽  
pp. 23-28
Author(s):  
A.I. Glushchenko ◽  
M.Yu. Serov
Keyword(s):  
Energy Efficiency ◽  
Control System ◽  
Comparative Analysis ◽  
Performance Optimization ◽  
Optimization Methods ◽  
Online Optimization ◽  
New Approach ◽  
Advantages And Disadvantages ◽  
Analysis Of Performance

В статье рассматривается вопрос совершенствования системы управления параллельно-работающими насосными агрегатами с целью повышения энергоэффективности их работы. Проведено сравнение и выявление недостатков существующих методов решения рассматриваемой проблемы. Предложена идея нового подхода на базе онлайн оптимизации. The problem under consideration is improvement of the energy efficiency of a control system of parallel-running pump units. Known methods used to solve this problem are considered. Their advantages and disadvantages are shown. Finally, the idea of a new approach, which is based on online optimization, is proposed.

scholarly journals Explaining participation in undeclared work in France: lessons for policy evaluation

2017 ◽  
Vol 37 (3/4) ◽  
pp. 203-217 ◽  
Author(s):  
Jan Windebank ◽  
Ioana Alexandra Horodnic
Keyword(s):  
Policy Framework ◽  
Small Scale ◽  
French Population ◽  
The European Union ◽  
Social Actor ◽  
Tax Morale ◽  
Content Type ◽  
Economic Actor ◽  
Undeclared Work

Purpose France is a model of best practice in the European Union as regards policy to combat undeclared work. The purpose of this paper is to take the country as a case study to evaluate the competing explanations of why people engage in undeclared work which underpin such policy, namely, the dominant rational-economic-actor approach and the more recent social-actor approach. Design/methodology/approach To evaluate these approaches, the results of 1,027 interviews undertaken in 2013 with a representative sample of the French population are analysed. Findings The finding is that higher perceived penalties and risks of detection have no significant impact on the likelihood of conducting undeclared work in France. In contrast, the level of tax morale has a significant impact on engagement in the activity: the higher the tax morale, the lower is the likelihood of participation in the undeclared economy. Higher penalties and risks of detection only decrease the likelihood of participation in undeclared work amongst the small minority of the French population with very low tax morale. Practical implications Current policy in France to counter undeclared work is informed principally by the rational-economic-actor approach based on a highly developed infrastructure for detection and significant penalties alongside incentives to declare small-scale own-account work. The present analysis suggests that this approach needs to be supplemented with measures to improve citizens’ commitment to compliance by enhancing tax morale. Originality/value This case study of a country with a well-developed policy framework to combat undeclared work provides evidence to support the social-actor approach for informing policy change.

Benchmarking the practices of flexibility with maturity models and frameworks of organizational capabilities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanjai Kumar Shukla ◽  
Sushil
Keyword(s):  
Information Technology ◽  
Comparative Analysis ◽  
Business Environment ◽  
Organizational Capabilities ◽  
Maturity Model ◽  
Human Capabilities ◽  
Maturity Models ◽  
Content Type ◽  
Wide Range ◽  
Flexibility Maturity

PurposeOrganizational capabilities are crucial to achieve the objectives. A plethora of maturity models is available to guide organizational capabilities that create a perplexing situation about what stuff to improve and what to leave. Therefore, a unified maturity model addressing a wide range of capabilities is a necessity. This paper establishes that a flexibility maturity model is an unified model containing the operational, strategic and human capabilities.Design/methodology/approachThis paper does a comparative analysis/benchmarking studies of different maturity models/frameworks widely used in the information technology (IT) sector with respect to the flexibility maturity model to establish its comprehensiveness and application in the organization to handle multiple goals.FindingsThis study confirms that the flexibility maturity model has the crucial elements of all the maturity models. If the organizations use the flexibility maturity model, they can avoid the burden of complying with multiple ones and become objective-driven rather than compliance-driven.Research limitations/implicationsThe maturity models used in information technology sectors are used. This work will inspire other maturity models to adopt flexibility phenomena.Practical implicationsThe comparative analysis will give confidence in application of flexibility framework. The business environment and strategic options across organizations are inherently different that the flexibility maturity model well handles.Social implicationsA choice is put to an organization to see the comparison tables produced in this paper and choose the right framework according to the prevailing business situation.Originality/valueThis is the first study that makes a conclusion based on comparative benchmarking of existing maturity models.

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