Exhaustive Enumeration Method Research Articles

Full-Control and Switching of Optical Fano Resonance by Continuum State Engineering.

Fano resonance, known for its unique asymmetric line shape, has gained significant attention in photonics, particularly in sensing applications. However, it remains difficult to achieve controllable Fano parameters with a simple geometric structure. Here, a novel approach of using a thin-film optical Fano resonator with a porous layer to generate entire spectral shapes from quasi-Lorentzian to Lorentzian to Fano is proposed and experimentally demonstrated. The glancing angle deposition technique is utilized to create a polarization-dependent Fano resonator. By altering the linear polarization between s- and p-polarization, a switchable Fano device between quasi-Lorentz state and negative Fano state is demonstrated. This change in spectral shape is advantageous for detecting materials with a low-refractive index. A bio-particle sensing experiment is conducted that demonstrates an enhanced signal-to-noise ratio and prediction accuracy. Finally, the challenge of optimizing the film-based Fano resonator due to intricate interplay among numerous parameters, including layer thicknesses, porosity, and materials selection, is addressed. The inverse design tool is developed based on a multilayer perceptron model that allows fast computation for all ranges of Fano parameters. The method provides improved accuracy of the mean validation factor (MVF = 0.07, q-q') compared to theconventional exhaustive enumeration method (MVF = 0.37).

Designing an ACS by Applying Galvanic Coatings Based on Solving the Optimization Problem

An automated control system for the technological process of applying galvanic coatings to a variety of cathode parts of various shapes and sizes is considered based on solving the problem of finding the optimal arrangement of the parts in a galvanic bath to obtain coatings with the minimum value of criterion R—the ratio of the number of rejected parts Nreject to the total number of parts N placed on the suspension device. To solve the problem, a calculation-logical system is developed that uses the exhaustive enumeration method, the Gomory algorithm modified by the authors, and the branch-and-bound method. When solving the problem, the Gomory algorithm is found to be the best algorithm among the three methods in terms of performance. A two-level control system for the galvanic process in a bath with a suspension device is developed.

A Holistic Formulation for System Margining and Jitter Tolerance Optimization in Industrial Post-Silicon Validation

There is an increasingly higher number of mixed-signal circuits within microprocessors and systems on chip (SoC). A significant portion of them corresponds to high-speed input/output (HSIO) links. Post-silicon validation of HSIO links can be critical for making a product release qualification decision under aggressive launch schedules. The optimization of receiver analog circuitry in modern HSIO links is a very time consuming post-silicon validation process. Current industrial practices are based on exhaustive enumeration methods to improve either the system margins or the jitter tolerance compliance test. In this paper, these two requirements are addressed in a holistic optimization-based approach. We propose a novel objective function based on these two metrics. Our method employs Kriging to build a surrogate model based on system margining and jitter tolerance measurements. The proposed method, tested with three different realistic server HSIO links, is able to deliver optimal system margins and guarantee jitter tolerance compliance while substantially decreasing the typical post-silicon validation time.

Estimating peak water demand: Literature review of current standing and research challenges

Abstract Since the 1940s, the models used to estimate peak water demand has been based largely upon variations and refinements of the probabilistic ‘fixture unit’ model. An approach originally advanced by Hunter (1940) in the United States of America (USA). Seeking an improved approach to the 'fixture unit' model, now widely recognised as outdated, is the key driving force behind the current work. Boosted by the development of computing power, the plumbing industry, researchers, and academics have, over the last decade, developed computational models as a means of estimating peak water demand. This paper builds on computational models embracing the estimation of peak water demand. A brief outline of the fixture unit and its limitations is provided with key developments in computational modeling comprising current developments from the USA and UK. A brief outline of computational models is presented: Modified Wistort Method (MWM); the Exhaustive Enumeration Method (EEM), and the Water Demand Calculator (WDC). Also presented, from the UK, is the Loading Unit Normalisation Assessment method (LUNA) aimed at an improved model to size domestic hot and cold-water systems. The analysis of the computational models suggests the WDC model is conceivably the most compatible with that of the plumbing industry's design requirements. Suggesting this model could easily be adapted to meet the requirements across international borders. Challenges for the international acceptance of the WDC are the field study requirements to determine p (probability of use) and q (fixture flow rate) values for all types of buildings.

Simulation Model in Markovian Decision Theory in Allocation Optimization in Nigerian River Basin Development

The work applied Simulation Modeling in Markovian Decision Theory, adapts infinite models of exhaustive enumeration method for the solution of allocation optimization in multi-purpose and multi-objective Nigerian River Basin Development Authorities, RBDAs’ planning and management problems by logically apportioning levels of development to various purposes while optimizing eight objectives in stages. This type of management problem is a decision problem and cannot be handled by linear programming which can only optimize one objective at a time. Methodology involves methods and experiments, data were collected from the River Basin Development Authorities, Ministries and Parastatals. Markov chain was used to assess solution. The result of the experiments shows policy 10, worst conflict condition calls for application of maintenance whenever the River Basin Engineering Development is in state 8 or very poor which interprets that development should be logically apportioned by the planning and management engineer as follows: Irrigated Agriculture-N3.86b, Water Supply-N8.82b, Hydropower-N13.42b, Flood Control-N17.52b, Drainages-N23.16b, Navigation-N25.58b, Recreation-N45.84b, Erosion Control-N61.84b. While E 10 represents expected yearly benefit: when the River Basin Engineering Development is apportioned as above stated from the limited available fund of the Federal Government Budget of N 200billon, at least a (revenue) benefit of N 1.108Trillion can be achieved under the worst condition of conflict objectives. This work also advises a maintenance programme for the River Basin in accordance with the result of experiments because the Basin should operate a minimum of 8years and a maximum of 21 year for full capacity utilization of assets. Keywords : Simulation, allocation, optimization, Markov chain, River Basin Development DOI : 10.7176/JRDM/53-05 Publication date :March 31 st 2019

Emergency Service Vehicle Location Problem with Batch Arrival of Demands

In this paper an emergency service vehicle (ESV) location problem has been considered in which it is assumed that each emergency call may require more than one ESV. In ESV location problem two factors should be known; the location of stations and the number of ESVs at each station. Hence, a nonlinear mixed integer programming model is presented in order to maximize the total response rate to the emergency calls. Moreover, a solution method based on genetic algorithm is provided and efficiency of the algorithm is evaluated with regard to the results from an exhaustive enumeration method. The model is applied to the real case study based on the data from Mashhad city to find the emergency gas stations and the required ESVs. Finally, a sensitivity analysis on the main parameters of the model is conducted and the managerial insights were reported. The results indicate that considering the fact that each call may require more than one ESV is very influential on the response rate and the assumption of each call requires just one ESV makes the results unrealistic.

Reliable Intermodal Freight Network Expansion with Demand Uncertainties and Network Disruptions

This paper develops a robust Mixed-Integer Linear Program (MILP) to assist railroad operators with intermodal network expansion decisions. Specifically, the objective of the model is to identify critical rail links to retrofit, locations to establish new terminals, and existing terminals to expand, where the intermodal freight network is subject to demand and supply uncertainties. Additional considerations by the model include a finite overall budget for investment, limited capacities on network links and at intermodal terminals, and time window constraints for shipments. A hybrid Genetic Algorithm (GA) is developed to solve the proposed MILP. It utilizes a column generation algorithm to solve the freight flow assignment problem and a multi-modal shortest path label-setting algorithm to solve the pricing sub-problems. An exact exhaustive enumeration method is used to validate the GA results. Experimental results indicate that the developed algorithm is capable of producing optimal solutions efficiently for small-sized intermodal freight networks. The impact of uncertainty on network configuration is discussed for a larger-sized case study.

Optimal Placement of Sensors and Actuators for Gyroelastic Body Using Genetic Algorithms

A flexible body with a distribution of stored angular momentum is viewed as a gyroelastic body. The flexible structure may require active vibration suppression, which can be controlled using a collection of control moment gyroscopes. This study investigates the optimal placement of collocated angular rate sensors and control moment gyroscope actuators for a constrained gyroelastic body based on genetic algorithms. First, the dynamics and modal analysis of the constrained gyroelastic body are presented. The state-space model is adopted that contains the distribution of actuators and sensors. Based on the concept of the controllability and the observability of the gyroelastic system, the objective functions are proposed aiming at the maximization of the controllability and observability of the constrained gyroelastic system. For situations with a fixed number of actuators and sensors, an exhaustive enumeration method and genetic algorithms are used to determine the locations of actuators and sensors. For a comprehensive optimization of the number and locations of actuator–sensor pairs, genetic algorithms are used to avoid calculating all possible combinations, increasing factorially in the enumeration method. The optimized results are verified by the responses of the constrained gyroelastic body. Numerical simulations are presented for a cantilevered plate.

Energy oriented multi cutting parameter optimization in face milling

A new model for evaluating the energy consumed by a machine tool for processing a prismatic workpiece was developed. The model takes into account the energy absorbed by different machine components such as the auxiliary systems, the axes, the axes chiller, the tool change system, chip conveyor and the spindle system. The relationships between the power absorption of each considered machine component and the main cutting parameters were adequately modeled. The cutting energy was also taken into consideration. Since the wear of the tool was included in the model, the energy absorbed by the machine during passive phases (e.g. tool changes) was also evaluated. Each machine component model was opportunely configured according to the considered production phase. Some of the parameters of the machine tool energy model were identified through experimental tests performed on a real machining center equipped with linear motors. A multivariable energy optimization was carried out considering the cutting speed, the feed and the radial depth of cut as the main parameters. The energy minimization was performed through exhaustive enumeration methods. Results were properly discussed and analyzed. The optimization analysis was also repeated emulating various machine tool configurations and different production scenarios.

A bi-level programming model for protection of hierarchical facilities under imminent attacks

Disorders caused by deliberate sabotage and terrorist attacks have always been considered as a major threat by the governments. Hence, identifying and planning for strengthening of critical facilities have become a priority for more security and safety. This paper presents a bi-level formulation of the r-interdiction median problem with fortification for critical hierarchical facilities. In the developed bi-level formulation, the defender, as the leader, decides to protect a certain number of facilities in each level of the hierarchical system in order to minimize the impact of the most disruptive attacks to unprotected facilities. On the other hand the attacker, as the follower, with full information about protected facilities, makes his interdiction plan to maximize the total post-attack cost incurred to the defender. We develop three metaheuristic algorithms and an exhaustive enumeration method to solve the introduced problem. Extensive computational tests on a set of randomly generated instances demonstrate the effectiveness of the developed algorithms.

Optimal design of reinforced concrete beams: A review

This paper summarizes available literature on the optimization of reinforced concrete (RC) beams. The objective of optimization (e.g. minimum cost or weight), the design variables and the constraints considered by different studies vary widely and therefore, different optimization methods have been employed to provide the optimal design of RC beams, whether as isolated structural components or as part of a structural frame. The review of literature suggests that nonlinear deterministic approaches can be efficiently employed to provide optimal design of RC beams, given the small number of variables. This paper also presents spreadsheet implementation of cost optimization of RC beams in the familiar MS Excel environment to illustrate the efficiency of the exhaustive enumeration method for such small discrete search spaces and to promote its use by engineers and researchers. Furthermore, a sensitivity analysis is performed on the contribution of various design parameters to the variability of the overall cost of RC beams.

Estimation of Glomerular Podocyte Number

The podocyte depletion hypothesis has emerged as an important unifying concept in glomerular pathology. The estimation of podocyte number is therefore often a critical component of studies of progressive renal diseases. Despite this, there is little uniformity in the biomedical literature with regard to the methods used to estimate this important parameter. Here we review a selection of valid methods for estimating podocyte number: exhaustive enumeration method, Weibel and Gomez method, disector/Cavalieri combination, disector/fractionator combination, and thick-and-thin section method. We propose the use of the disector/fractionator method for studies in which controlled sectioning of tissue is feasible, reserving the Weibel and Gomez method for studies based on archival or routine pathology material.

Incorporating the threat of terrorist attacks in the design of public service facility networks

In this paper, we consider the design problem of a public service facility network with existing facilities when there is a threat of possible terrorist attacks. The aim of the system planner, who is responsible for the operation of the network, is to open new facilities, relocate existing ones if necessary, and protect some of the facilities to ensure a maximum coverage of the demand that is assumed to be aggregated at customer zones. By doing so, the system planner anticipates that a number of unprotected facilities will be rendered out-of-service by terrorist attacks. It is assumed that the sum of the fixed cost of opening new facilities, the relocation costs, and the protection costs cannot exceed a predetermined budget level. Adopting the approach of gradual (or partial) coverage, we formulate a bilevel programming model where the system planner is the leader and the attacker is the follower. The objective of the former is the maximization of the total service coverage, whereas the latter wants to minimize it. We propose a heuristic solution procedure based on tabu search where the search space consists of the decisions of the system planner, and the corresponding objective value is computed by optimally solving the attacker’s problem using CPLEX. To assess the quality of the solutions produced by the tabu search (TS) heuristic, we also develop an exhaustive enumeration method, which explores all the possible combinations of opening new facilities, relocating existing ones, and protecting them. Since its time complexity is exponential, it can only be used for relatively small instances. Therefore, to be used as a benchmark method, we also implement a hill climbing procedure employed with the same type of moves as the TS heuristic. Besides, we carry out a sensitivity analysis on some of the problem parameters to investigate their effect on the solution characteristics.

An Optimization Model for Crucial Key Pipes and Mechanical Reliability: A Case Study on a Water Distribution System in Taiwan

This study develops a new method to calculate the water distribution system’s mechanical reliability and locates crucial pipes by using the minimum cut-sets method, exhaustive enumeration method and an optimal allocation model. First, a full domain optimization model was established to analyze the water distribution system. Next, the minimum cut-sets method and exhaustive enumeration method were used to discover the water distribution system’s key pipes. At last, water distribution system’s mechanical reliability can be calculated. The major contributions are that we can use optimal allocation model to locate crucial pipelines in the water distribution whose failure will severely impair the source-demand connectivity. Besides, we can calculate water distribution system’s mechanical reliability. Thus we can offer these results for hydraulic construction funds consulting. The developed methodology is applied to a water distribution system in Hsin-Chu, Taiwan.

A new approach to solve a mixed-model assembly line with a bypass subline sequencing problem

To meet the diversification of customer’s preferences, mixed-model assembly lines are installed in many manufacturing plants. In some of them, a large variation exists in assembly times among different product types. The large variation reduces production efficiency and may cause a line stoppage. These variations can be reduced by installing a bypass subline which processes a portion of assembly operations of products with relatively longer assembly times. In spite of its significance, sequencing problem on bypass subline rarely has been discussed in the literature. This paper addresses a sequencing problem with a bypass subline with the goals of leveling the part usage rates and reducing line stoppages. A novel hybrid algorithm incorporating genetic algorithm and event-based procedure is developed to solve the problem. Efficiency of the proposed algorithm is demonstrated through solving several test problems and comparing the resulted solutions with optimal solutions obtained from an exhaustive enumeration method.

High-Level Synthesis of VLSI Processors for Intelligent Integrated Systems Based on Logic-in-Memory Structure

One of the most serious problems in recent VLSI systems is data transfer bottleneck between memories and processing elements. To solve the problem, a model of highly parallel VLSI processors for intelligent integrated systems is presented. A logic-in-memory module composed of a processing element, a register and a local memory is defined as a basic building block to form a regular parallel structure. The data transfer between adjacent modules are done simply in a single clock period by a shift-register chain.A high-level synthesis method is discussed on the hardware model, when a data-dependency graph corresponding to a processing algorithm is given. We must simultaneously consider both scheduling and allocation for the time optimization problem under a constraint of an chip area. That is, we consider the best scheduling together with allocation such that the processing time becomes minimum under a constraint of a fixed number of modules. Not only an exhaustive enumeration method but also a branch-and-bound method is proposed for the problem. As a result, it is made clear that the proposed high-level synthesis method is very effective to design special-purpose VLSI processors free from data transfer bottleneck.

File and workload allocation design for distributed database on a two-level local multi-access computer network

This paper presents an analytical model to allocate files and workload simultaneously among heterogeneous servers that operate distributed databases on a two-level local multi-access computer network. The allocation problem is presented in the form of a non-linear integer programming model. The model incorporates both local processing and data communication overhead. The problem is NP-complete and thus a heuristic is developed. To illustrate its suitability, the heuristic is compared with an exhaustive enumeration method for small problems and with a genetic algorithm for large problems. Computational results imply that the heuristic provide effective database designs.

File and workload allocation on a local multi-access computer network: incorporating local processing and communication overhead

The paper presents an analytical model to allocate files and workload simultaneously among heterogeneous servers for a distributed database where the servers are connected by a local multi-access computer network. The allocation problem is presented in the form of a nonlinear integer programming model. The model incorporates both local processing and communication overhead. The problem is proved to be NP-complete and thus a heuristic is developed. To illustrate its suitability, the heuristic is compared with an exhaustive enumeration method for small problems and with a genetic algorithm for large problems. Computational results demonstrate that the proposed model and heuristic provide effective database designs

An algorithm for the con due-date determination and sequencing problem

For a set of n jobs with deterministic processing times and common starting times, the problem is to determine the optimal constant flow allowance k ∗ for the CON due-date assignment method and the optimal sequence σ ∗ which minimizes the weighted average of missed due-dates. As k ∗ and σ ∗ cannot be independently determined, we propose an algorithm which systematically searches for the optimal solution. Although the algorithm has time complexity of 0(2 n n 2), it is considerably more efficient than the exhaustive enumeration method which considers all n! possible sequences.