Hybrid flowshop scheduling with machine and resource-dependent processing times

Most of research in production scheduling is concerned with the optimization of a single criterion. However the analysis of the performance of a schedule often involves more than one aspect and therefore requires a multi-objective treatment. In this research, with combination of two multiple objective decision-making methods, min–max and weighted techniques, a new solution presentation method and a robust hybrid metaheuristic, we solved sequence-dependent setup time hybrid flowshop scheduling problems. In this paper for reflecting real-world situation adequately, we assume the processing time of each job depends on the speed of machine and amount of resource allocated to each machine at the stage which is processed on it. In formulation of min–max type, the decision-maker can have the flexibility of mixed use of weights and distance parameter in expressing desired improvement on produced Pareto optimal solutions. To minimize makespan and total resource allocation costs, the proposed hybrid approach is robust, fast, and simply structured, and comprises two components: genetic algorithm and a variable neighborhood search. The comparison shows the proposal to be very efficient for different structure instances.     

Bi-criteria assembly line balancing by considering flexible operation times

This paper addresses a novel approach to deal with Flexible task Time Assembly Line Balancing Problem (FTALBP). In this regard, machines are considered in which operation time of each task can be between lower and upper bounds. These machines can compress the processing time of tasks, but this action may lead to higher cost due to cumulative wear, erosion, fatigue and so on. This cost is described in terms of task time via a linear function. Hence, a bi-criteria nonlinear integer programming model is developed which comprises two inconsistent objective functions: minimizing the cycle time and minimizing the machine total costs. In order to sustain these objectives concurrently, this paper applies the LP-metric method to make a combined dimensionless objective. Moreover, a genetic algorithm (GA) is presented to solve this NP-hard problem and design of experiments (DOE) method is hired to tune various parameters of our proposed algorithm. The computational results demonstrate the effectiveness of implemented procedures.     

Graphical Representations of Speed: Obstacles Preservice K‐8 Teachers Experience

This study examines the difficulties college students experience when creating and interpreting graphs in which speed is one of the variables. Nineteen students, all preservice elementary or middle school teachers, completed an upper‐level course exploring algebraic concepts. Although all of these preservice teachers had previously completed several mathematics courses, including calculus, they demonstrated widespread misconceptions about the variable speed. This study identifies four cognitive obstacles held by the students, provides excerpts of their graphical constructions and verbal interpretations, and discusses potential causes for the confusion. In particular, misconceptions arose when students interpreted the behavior and nature of speed within a graphical context, as well as in situations where they were required to construct a graph involving speed as a variable. The study concludes by offering implications for the teaching and learning of speed and its interpretation within a graphical setting.     

Apple – biomorphic synthesis of porous ZnO nanostructures for glucose direct electrochemical biosensor

Biomorphic porous ZnO nanostructures were successfully synthesized via an aqueous sol–gel soaking process using pieces of apple flesh and skin as templates and employed for glucose direct electrochemical biosensor. The structure and morphology of ZnO nanostructures were characterized by X-ray diffraction (XRD) and scanning electron microscope (SEM). By modifying glassy carbon electrode with the biomorphic ZnO nanostructures and Nafion, two glucose biosensors were constructed and their direct electrochemistry of glucose oxidase (GOD) was successfully investigated by cyclic voltammetry (CV). The biomorphic porous ZnO nanostructures using apple skin template (S-ZnO) were more effective in facilitating the electron transfer of immobilized GOD than that of using flesh apple template (F-ZnO). This may be a result of the unique morphology and smaller average crystallite size of the S-ZnO nanostructure. GOD immobilized on Nafion-porous S-ZnO nanostructure composite display direct, reversible, and surface-controlled redox reaction with a detection limit of 10 μM, a response time of 7 s, high sensitivity of 23.4 μA/mM cm² and a fast heterogeneous electron transfer rate with a rate constant (k_s) of 3.9 s^?1. It was found that S-ZnO significantly has improved the direct electron transfer between GOD and glassy carbon electrode with good stability and reproducibility.     

PEGylated Luminescent Gold Nanoclusters: Synthesis,Characterization, Bioconjugation,and Application to One‐ and Two‐Photon Cellular Imaging

Biocompatible, near‐infrared luminescent gold nanoclusters (AuNCs) are synthesized directly in water using poly(ethylene glycol)‐dithiolane ligands terminating in either a carboxyl, amine, azide, or methoxy group. The ≈1.5 nm diameter AuNCs fluoresce at ≈820 nm with quantum yields that range from 4–8%, depending on the terminal functional group present, and display average luminescence lifetimes approaching 1.5 μs. The two‐photon absorption (TPA) cross‐section and two‐photon excited fluorescence (TPEF) properties are also measured. Long‐term testing shows the poly(ethylene glycol) stabilized AuNCs maintain colloidal stability in a variety of media ranging from saline to tissue culture growth medium along with tolerating storage of up to 2 years. DNA and dye‐conjugation reactions confirm that the carboxyl, amine, and azide groups can be utilized on the AuNCs for carbodiimide, succinimidyl ester, and Cu^I‐assisted cycloaddition chemistry, respectively. High signal‐to‐noise one‐ and two‐photon cellular imaging is demonstrated. The AuNCs exhibit outstanding photophysical stability during continuous‐extended imaging. Concomitant cellular viability testing shows that the AuNCs also elicit minimal cytotoxicity. Further biological applications for these luminescent nanoclustered materials are discussed.     

A new heuristic for resource-constrained project scheduling in stochastic networks using critical chain concept

This paper presents a newly developed resource-constrained project scheduling method in stochastic networks by merging the new and traditional resource management methods. In each project, the activities consume various types of resources with fixed capacities. The duration of each activity is a random variable with a given density function. Since the backward pass method is implemented for feeding-in resources. The problem is to determine the finish time of each activity instead of its start time. The objective of the presented model is defined as minimizing the multiplication of expected project duration and its variance. The values of activities finish times are determined at decision points when at least one activity is ready to be operated and there are available resources. If at a certain point of time, more than one activity is ready to be operated but available resources are lacking, a competition among ready activities is carried out in order to select the activities which must be operated first. This paper suggests a competition routine by implementing a policy to maximize the total contribution of selected activities in reducing the expected project duration and its variance. In this respect, a heuristic algorithm is developed and compared with the other existing methods.