A variable neighbourhood search algorithm for the flexible job-shop scheduling problem

The flexible job-shop scheduling problem (FJSP) is a generalisation of the classical job-shop scheduling problem which allows an operation of each job to be executed by any machine out of a set of available machines. FJSP consists of two sub-problems which are assigning each operation to a machine out of a set of capable machines (routing sub-problem) and sequencing the assigned operations on the machines (sequencing sub-problem). This paper proposes a variable neighbourhood search (VNS) algorithm that solves the FJSP to minimise makespan. In the process of the presented algorithm, various neighbourhood structures related to assignment and sequencing problems are used for generating neighbouring solutions. To compare our algorithm with previous ones, an extensive computational study on 181 benchmark problems has been conducted. The results obtained from the presented algorithm are quite comparable to those obtained by the best-known algorithms for FJSP.     

A set partitioning based heuristic procedure for incremental cell formation with routing flexibility

One of the important issues regarding the implementation of cellular manufacturing relates to deciding whether to convert an existing job shop into a cellular manufacturing system comprehensively in a single go, or to convert in stages incrementally wherein the cells are formed one after the other taking the advantage of experiences of implementation. In this paper, a heuristic method based on iterative set partitioning is proposed for incremental cell formation where part operations can be processed on alternative machines. The objective is to minimize cycle time for a given number of workstations. The proposed method is numerically compared with the existing branch and bound technique and another heuristic algorithm based on multistage programming. It is found that the proposed method requires significantly less computational efforts to yield the optimal solution.     

Functional Description of Read-out Electronics for Time-Domain Multiplexed Bolometers for Millimeter and Sub-millimeter Astronomy

We have developed multi-channel electronics (MCE) which work in concert with time-domain multiplexors developed at NIST, to control and read signals from large format bolometer arrays of superconducting transition edge sensors (TESs). These electronics were developed as part of the Submillimeter Common-User Bolometer Array-2 (SCUBA2 ) camera, but are now used in several other instruments. The main advantages of these electronics compared to earlier versions is that they are multi-channel, fully programmable, suited for remote operations and provide a clean geometry, with no electrical cabling outside of the Faraday cage formed by the cryostat and the electronics chassis. The MCE is used to determine the optimal operating points for the TES and the superconducting quantum interference device (SQUID) amplifiers autonomously. During observation, the MCE execute a running PID-servo and apply to each first stage SQUID a feedback signal necessary to keep the system in a linear regime at optimal gain. The feedback and error signals from a ～1000-pixel array can be written to hard drive at up to 2 kHz.     

A DEA approach for comparing solution efficiency in U-line balancing problem using goal programming

Line balancing problem plays an important role in the decision making process to increase efficiency and productivity. Recently, U-shaped layout in many production lines has replaced the traditional straight line layout using just-in-time concept. Here, we propose a model, using multi-objective decision making approach to the U-shaped line balancing problem, to offer enhanced decision maker flexibility, by allowing for conflicting goals. The assembly line operation efficiency is the most significant aim in our study, and this efficiency relates to management of resources and the solution of line balancing problem. First, the U-shaped line balancing problem is solved considering the model's goals. Then, the index function of assembly line balancing is determined and the efficiencies of the optimal solution outputs are evaluated using data envelopment analysis (DEA). Finally, the discrimination weakness and distribution of illogical weight in simple DEA models are resolved using a mixed method.     

Buffer allocation in unreliable production lines based on design of experiments, simulation, and genetic algorithm

This paper presents a multiobjective formulation of the buffer allocation problem in unreliable production lines. Majority of the solution methods for buffer allocation problems assume that the process times, time between failures, and repair times are deterministic or exponentially distributed. This paper relaxes these restrictions by proposing a simulation-based methodology which can consider general function distributions for all parameters of production lines. Factorial design has been used to build a meta-model for estimating production rate based on a detailed, discrete event simulation model. We use genetic algorithm combined to line search method to solve the multiobjective model and determining the optimal (or near optimal) size of each buffer storage.     

Thermal behavior and entropy generation rate analysis of a viscous flow in MHD micropumps

Studying the effects of various parameters on the behavior of velocity, temperature and thus the entropy generation rate in the microfluidic systems to reduce loss power is very important. Minimization of entropy generation in the flow system enables us for the parametric optimization of the MHD micropumps operation. In the present study, a transient, laminar and fully developed electrically conductive fluid flow in MHD micropumps has been investigated and the temperature distribution and effects of dimensionless influencing parameters on the entropy generation rate has been presented. Pumping operator in MHD micropumps are the Lorentz forces, which is produced as a result of the interaction between magnetic and electric fields. Governing equations have been solved numerically using finite-difference (ADI) method. The results of simulation have shown good agreement with analytical results by ei-genfunction expansion method. In addition, the results are compared with experimental data from literature which confirms the accuracy of the model. The obtained results showed that aspect ratio, Hartman, Prandtl, Eckert numbers and Joule heating parameter have significant influences on the flow and temperature distribution as well as entropy generation rate in MHD micropumps that controlling them can lead us for optimized operation of MHD micropumps.

     

An Unreacted Shrinking Core Model for Calcination and Similar Solid-to-Gas Reactions

A variation on the unreacted shrinking core model has been developed for calcination and similar non-catalytic solid-to-gas decomposition reactions in which no gaseous reactant is involved and the reaction rate decreases with increasing product gas concentration. The numerical solution of the model has been validated against an analytical solution for the isothermal case. The model parameters have been tuned using literature data for the thermal dehydration (calcination) of gibbsite to alumina over a wide range of temperatures, from 490 to 923 K. The model results for gibbsite conversion agreed well with the published experimental data. A reaction order with respect to water vapor concentration of n = ?1 was found to give a good fit to the data and yield activation energies consistent with literature values. Predictions of the non-isothermal unreacted shrinking core model compare well with a more complex distributed model developed previously by the authors.     

Preparation and characterization of a temperature-sensitive nonwoven poly (propylene) with antibacterial properties

In this study, a temperature-sensitive fabric with antibacterial properties was prepared by the formation of silver nanoparticles (AgNPs) on nonwoven poly (propylene) (PP) grafted with poly (N-iso-propylacrylamide) (PNIPAAm-PP). First, PNIPAAm was grafted onto corona-treated nonwoven PP. Afterwards, silver nanoparticles were synthesized on the temperature-sensitive hydrogel layer grafted to the surface of nonwoven PP by the reduction of silver ions (Ag⁺). Fourier transform infra-red spectroscopy confirmed the presence of PNIPAAm on the nonwoven PP. scanning electron microscopy-energy dispersive X-ray spectroscopy was used to investigate surface morphology and the presence of silver particles in the samples. Inductively coupled-plasma atomic emission spectroscopy revealed that the Ag content in Ag-functionalized PNIPAAm-PP was significantly higher than Ag-functionalized corona-treated PP with the same concentration of silver solution. Moreover, the results of the swelling rate experiment confirmed that PNIPAAm-PP maintained temperature-sensitive properties after functionalizing with Ag. The results showed that the formation of AgNPs with enhancement in antibacterial property was possible onto PNIPAAm-PP.     

Effect of Fiber Acid Treatment on the Dynamic Mechanical Properties of Unsaturated Polyester/Carbon Fiber Unidirectional Composites

In this study, the surface modification of carbon fiber by sulfuric acid is investigated. Atomic Force Microscopy was employed to capture the corresponding changes in the surface roughness of the carbon fiber. Moreover, using treated and untreated fibers, unsaturated polyester unidirectional composite rods were prepared and their flexural properties were determined by three-point bending and dynamic mechanical thermal analysis.

The results indicated that the carbon fiber surface roughness increases in all samples. It is also found that treating the fiber decreases the magnitude of loss modulus. Besides, the flexural strength of composites made of the treated carbon fiber significantly increased.     

A genetic algorithm for the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties

In this paper, we consider the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties, with no machine idle time. The problem is strongly NP-hard. We proposed a new mathematical model, with non-linear terms and integer variables. We develop a genetic algorithm for solving the problem in medium and large size. The proposed procedure is compared with optimal solutions for the smaller instance sizes. The genetic procedure is also quite close to the optimum and provided an optimal solution for most of the test problems. Numerical examples show that the proposed algorithm is efficient and effective. Scheduling with early and tardy penalties has received extensive attention from the scheduling community because of its practical significance. Single machine scheduling environments actually occur in several practical applications. Also, the performance of many production systems is often determined by the schedules for a single bottleneck machine. Furthermore, the study of single machine problems frequently provides outcomes that prove functional for more complex scheduling areas.