IT-assisted equipment safety checks system to improve compliance: A case study at a distribution center

2013 ◽  
Vol 60 ◽  
pp. 77-86 ◽  
Author(s):  
David T. Goomas ◽  
Paul H.P. Yeow
Keyword(s):  
Distribution Center ◽  
Equipment Safety ◽  
Improve Compliance

scholarly journals Two-Phase Optimization Method for Determining Distribution Center Locations and Distribution Routes (Case Study: X Ltd.)

2020 ◽  
Vol 0 (5) ◽  
pp. 45
Author(s):  
Muhammad Rayhan Azzindani ◽  
Nabila Fajri Kusuma Ningrum ◽  
Mega Rizkah Sudiar ◽  
Anak Agung Ngurah Perwira Redi
Keyword(s):  
Optimization Method ◽  
Distribution Center ◽  
Two Phase ◽  
Phase Optimization

scholarly journals Mathematical Optimization Model for Truck Scheduling in a Distribution Center with a Mixed Service-Mode Dock Area

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Gustavo Correa Issi ◽  
Rodrigo Linfati ◽  
John Willmer Escobar
Keyword(s):  
Mathematical Optimization ◽  
Distribution Center ◽  
Mixed Integer ◽  
Cross Docking ◽  
Truck Scheduling ◽  
Logistics Strategy ◽  
Service Mode ◽  
Reducing Costs ◽  
And Storage

Cross-docking is a logistics strategy in which products arriving at a distribution center are unloaded from inbound trucks and sorted for transfer directly to outbound trucks, reducing costs and storage and product handling times. This paper addresses a cross-docking problem by designing a mixed-integer linear programming (MILP) model to determine a schedule for inbound and outbound trucks in a mixed service-mode dock area that minimizes the time from when the first inbound truck arrives until the last outbound truck departs (makespan). The model is developed using AMPL software with the CPLEX and Gurobi solvers, which provide results for different instances, most of these with actual shift data from an integrated distribution center of a multinational food company located in Concepción, Chile. The results obtained from the case study are notable and show the effectiveness of the proposed mathematical model.

scholarly journals Balanced sampling of boxes from batches for assessing quality of fruits and vegetables in EU countries

2021 ◽  
Author(s):  
Sara Franceschi ◽  
Gianni Betti ◽  
Lorenzo Fattorini ◽  
Francesca Gagliardi ◽  
Gianni Montrone
Keyword(s):  
Simulation Study ◽  
Fruits And Vegetables ◽  
Central Italy ◽  
Statistical Properties ◽  
Distribution Center ◽  
Balanced Sampling ◽  
Eu Countries ◽  
Inclusion Probabilities

AbstractThe best evaluation for the proportion of defective units in a batch of fruits and vegetables can be achieved by an exhaustive checking of all the boxes in the batch, that is prohibitive to perform in most cases. Usually, only a sample of boxes is checked. In EU countries, EU regulations establish to estimate the proportion of defective units in a batch by the proportion of defective units in the sample, without giving any rule for selecting boxes. Therefore, results are highly dependent on the subjective choice of boxes. In the present study, an objective design-based approach is considered to select boxes from batches, adopting balanced spatial schemes with equal inclusion probabilities. The schemes are able to select samples of boxes evenly spread throughout the batch also ensuring good statistical properties for the proportion of defective units in the sample as estimator of the proportion of defective units in the batch. The performance of these strategies is evaluated by means of a simulation study performed on real and artificial batches of apples, peppers and strawberries. A case study is considered to estimate the proportion of defective units in a batch of courgettes stored in a distribution center of a supermarket chain in Central Italy.

scholarly journals A Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm in Distribution Center Location Selection: A Case Study in Agricultural Supply Chain

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 53
Author(s):  
Phan Thuy Kieu ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen ◽  
Thanh Phong Ho
Keyword(s):  
Supply Chain ◽  
Supply And Demand ◽  
Distribution Center ◽  
Compromise Solution ◽  
Analytic Hierarchy ◽  
Location Selection ◽  
Proposed Model ◽  
Hierarchy Process ◽  
Agricultural Supply

Logistics is an important service sector, contributing to improving the competitiveness of the economy. Therefore, along with increasing the application of technology and effective business models, it is necessary to increase the connectivity of the infrastructure systems of industrial parks, roads, and seaports of regions and the country. Over the past decades, Vietnamese businesses have been step-by-step going through many stages from production, packaging, quality, hygiene, and safety to grasping new stages in the domestic and global value chain. In many industries, businesses are increasing the content of their own designs, exploiting brands, and approaching consumption networks in the target market. The role of the distribution center is becoming more and more important in ensuring a seamless and flawless supply chain. In particular, the distribution center is the most sensitive contact point between supply and demand in each enterprise. Therefore, the key mission of a distribution center is to reconcile supply and demand requirements. Distribution center location selection problems usually involve multiple quantitative and qualitative criteria that the decision maker must take into account for assessing the symmetrical impact of the criteria to reach the most accurate result. In this study, the authors propose a hybrid MCDM model based on Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm to support the distribution location selection problem of perishable agricultural products. The proposed model is then applied to the numerical case study of the sweet potato product of the Mekong Delta region of Vietnam to demonstrate the feasibility of the model. The contribution of this research is to propose an MCDM model for improving the efficiency of the agricultural supply chain through selecting a location distribution center. This proposed model can be applied to the agricultural supply chain around the world.

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