Two-stage optimisation method for material flow and allocation management in cross-docking networks

Cross-docking is a relatively new logistics strategy in which items are moved from suppliers to customers through cross-docking centres without putting them into long-term storage. An important decision during the planning of cross-docking operations is related to the material flow management in the network, which has great potential to reduce transportation costs. However, until now, there has been a lack of studies regarding operations for both transportation of trucks between locations and trans-shipment of items in cross-docking centres. This study presents a novel two-stage mixed integer linear mathematical model for the transportation problem of cross-docking network design integrated with truck–door assignments to minimise total transportation costs from suppliers to customers. This model also considers incoming/outgoing truck-loading plans and product allocations in the cross-docking area with regard to the two-dimensional physical constraints. Due to the complexity of the problem, a genetic algorithm (GA) is proposed to solve large-sized problems. Computational studies are conducted to examine the validity of the two-stage model and performance of the GA. The computational studies show that the introduced model provides a comprehensive plan for material flow management in cross-docking networks and proposed GA is capable of obtaining effective results for the problem within a short computational time.     

A new approach for solution of vehicle routing problem with hard time window: an application in a supermarket chain

In this study, a vehicle routing problem with hard time windows (VRPHTW) that appears to meet demands of customers’ service within time intervals in a supermarket chain is solved. In VRPHTW, to reach a solution by an exact method is quite difficult and sometimes impossible if number of constraints is large enough (i.e., NP-hard), and solution time of a VRPHTW grows exponentially. As the size of the problem grows, a near optimal solution can be found using a heuristic method. A hierarchical approach consisting of two stages as “cluster-first route-second” is proposed. In the first stage, customers are assigned to vehicles using three different clustering algorithms (i.e., K-means, K-medoids and DBSCAN). In the second stage, a VRPHTW is solved using a MILP. The main contribution of the article is that the proposed hierarchical approach enables us to deal with a large size real problem and to solve it in a short time using the exact method. Finally, the proposed approach is employed on a supermarket chain. An instance of the algorithm is demonstrated to illustrate the applicability of the proposed approach and the results obtained are highly favourable.     

Preparation of submicron calcite particles by combined wet stirred media milling and ultrasonic treatment

This paper investigates the grindability of calcite powder (D₅₀ = 6.68 µm) to submicron particle sizes using stirred media mill (0.75 l) and ultrasonic generator (400 W, 24 kHz). The present study focuses directly on the comminution of calcite powder in water media by combined stirred milling and ultrasonic treatment and effects of some operational parameters such as grinding time (10–30 min), ultrasonic power (40–100% µm as amplitude settings), and solid ratio (10–30% w/w) on comminution. Experimental results have been evaluated on the basis of product size and width of particle size distribution.     

A Measurement and Structural Model for Usability Evaluation of Shared Workspace Groupware

This study presents the development process of a set of questionnaire items to establish a measurement model for the usability of shared workspace groupware systems, which is suggested as a usability scale called SWUS, the Shared Workspace Usability Scale. Manifest variables and latent variables are based on the various dimensions of teamwork collated through the literature. A structural model was built on the measurement model. Models were evaluated through PLS-SEM methods. Data acquired on candidate questionnaire items from 398 international respondents who are users of five different online collaborative word processors was used for the model analysis. Of 37 candidate manifest variables, 22 were retained, which were measuring seven latent constructs: “3C Mechanisms,” “Grounding,” “Team Integration,” “Communication,” “Shared Access,” “Awareness,” and “Usability.” The data provided empirical evidence for the structural model based on these latent variables. The responses of the participants were not sensitive to differences between users in terms of gender and native language but showed sensitivity to age, experience with the evaluated software, and different shared workspace groupware evaluated in the study. Our structural model attempts to integrate several frameworks and models of usability for CSCW environments and provides empirical evidence for its reliability and validity based on subjective responses from users of shared workspace groupware.     

An Application on Mobile Devices with Android and IOS Operating Systems Using Google Maps APIs for the Traveling Salesman Problem

Nowadays, the Traveling Salesman Problem (TSP) is one of the most studied combinational optimization problems that researchers study. Although it is easy to define, its solution is hard. Therefore, it is one of the NP-hard problems in the research literature. It can be used to solve real-life problems such as route planning and scheduling, and transportation and logistics applications. In this study, for TSP, an interface that can run on mobile devices using Android and IOS operating systems is developed. Real-world data are used online by the interface. Locations, and the distance between them, are obtained instantly by Google Maps APIs. Genetic (GA) and ant colony optimization (ACO) algorithms are used to solve the TSP. Furthermore, users have also been allowed to conduct trials for different parameter values. The application developed has been tested on two different datasets. The test results show that for the determination of the optimum route, the ACO algorithm is better than the GA. However, when considering the run times, GA works much faster than ACO.     

Photoluminescence characterization and heat treatment effect on luminescence behavior of BaTa2O6:Dy3+ phosphor

Undoped and Dy³⁺‐doped barium tantalate phosphors were synthesized by the solid‐state reaction method at 1425°C. Also, 10 mol% Dy³⁺‐doped BaTa₂O₆ was sintered between 1150 and 1425°C in order to determine temperature effect on structural and luminescence properties. Afterwards, they were characterized by XRD, SEM‐EDS and photoluminescence (PL) analyses. PL spectra exhibited the excitation peaks between 300 and 440 nm. Two typical emissions were observed at 486.2 nm (blue) and 577.7 nm (yellow) due to the ⁴F_9/2→⁶H_15/2 and ⁴F_9/2→⁶H_13/2 transitions, respectively. Emission intensities increased with increasing doping concentration of Dy³⁺ up to 10 mol% and then decreased due to the concentration quenching effect. Moreover, depending on the increase in heat treatment temperature, the intensity of emission reached maximum at 1425°C. The calculated CIE chromaticity coordinates of phosphors located in the white light region.