Improving Programming Skills Through an Innovative Collaborative Programming Model: A Case Study

Author(s):  
Lanqin Zheng
2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110106
Author(s):  
John Rios ◽  
Rodrigo Linfati ◽  
Daniel Morillo-Torres ◽  
Iván Derpich ◽  
Gustavo Gatica

An efficient distribution center (DC) is one that receives, stores, picks and packs products into new logistics units and then dispatches them to points of sale at the minimal operating cost. The picking and packing processes represent the highest operating cost of a DC, and both require a suitable space for their operation. An effective coordination between these zones prevents bottlenecks and has a direct impact on the DC’s operational results. In the existing literature, there are no studies that optimize the distribution of the picking and packing areas simultaneously while also reducing operating costs. This article proposes an integer nonlinear integer programming model that minimizes order preparation costs. It does so by predicting customer demand based on historical data and defining the ideal area for picking and packing activities. The model is validated through a real case study of seven clients and fifteen products. It achieves a [Formula: see text] reduction in operating costs when the optimal allocation of the picking and packing areas is made.


2017 ◽  
Vol 7 (2) ◽  
pp. 125 ◽  
Author(s):  
Thomas Staubitz ◽  
Ralf Teusner ◽  
Christoph Meinel ◽  
Nishanth Prakash

Programming tasks are an important part of teaching computer programming as they foster students to develop essential programming skills and techniques through practice.  The design of educational problems plays a crucial role in the extent to which the experiential knowledge is imparted to the learner both in terms of quality and quantity. Badly designed tasks have been known to put-off students from practicing programming. Hence, there is a need for carefully designed problems. Cellular Automata programming lends itself as a very suitable candidate among problems designed for programming practice. In this paper, we describe how various types of problems can be designed using concepts from Cellular Automata and discuss the features which make them good practice problems with regard to instructional pedagogy. We also present a case study on a Cellular Automata programming exercise used in a MOOC on Test Driven Development using JUnit, and discuss the automated evaluation of code submissions and the feedback about the reception of this exercise by participants in this course. Finally, we suggest two ideas to facilitate an easier approach of creating such programming exercises.


Author(s):  
Diego Gabriel Rossit ◽  
Sergio Nesmachnow ◽  
Jamal Toutouh

Enhancing efficiency in Municipal Solid Waste (MSW) management is crucial for local governments, which are generally in charge of collection, since this activity explains a large proportion of their budgetary expenses. The incorporation of decision support tools can contribute to improve the MSW system, specially by reducing the required investment of funds. This article proposes a mathematical formulation, based on integer programming, to determine the location of garbage accumulation points while minimizing the expenses of the system, i.e., the installment cost of bins and the required number of visits the collection vehicle which is related with the routing cost of the collection. The model was tested in some scenarios of an important Argentinian city that stills has a door-to-door system, including instances with unsorted waste, which is the current situation of the city, and also instances with source classified waste. Although the scenarios with classified waste evidenced to be more challenging for the proposed resolution approach, a set of solutions was provided in all scenarios. These solutions can be used as a starting point for migrating from the current door-to-door system to a community bins system.


2012 ◽  
Vol 52 (No. 2) ◽  
pp. 51-66 ◽  
Author(s):  
P. Havlík ◽  
F. Jacquet ◽  
Boisson J-M ◽  
S. Hejduk ◽  
P. Veselý

BEGRAB_PRO.1 – a mathematical programming model for BEef and GRAssland Biodiversity PRoduction Optimisation – elaborated for analysis of organic suckler cow farms in the Protected Landscape Area White Carpathians, the Czech Republic, is presented and applied to the analysis of jointness between several environmental goods. In this way, the paper complements recent studies on jointness between commodities and non-commodities. If these goods are joint in production, agri-environmental payments must be carefully designed because they do not influence only production of the environmental good they are intended for but also the production of other environmental goods. If jointness is negative, any increase in the payment for an environmental good leads to a decrease in production of other environmental goods.


2018 ◽  
Vol 64 (No. 7) ◽  
pp. 316-327 ◽  
Author(s):  
You Peng-Sheng ◽  
Hsieh Yi-Chih

To order to raise chickens for meat, chicken farmers must select an appropriate breed and determine how many broilers to raise in each henhouse. This study proposes a mathematical programming model to develop a production planning and harvesting schedule for chicken farmers. The production planning comprises the number of batches of chickens to be raised in each henhouse, the number of chicks to be raised for each batch, what breed of chicken to raise, when to start raising and the duration of the raising period. The harvesting schedule focuses on when to harvest and how many broilers to harvest each time. Our aim was to develop proper production and harvesting schedules that enable chicken farmers to maximise profits over a planning period. The problem is a highly complicated one. We developed a hybrid heuristic approach to address the issue. The computational results have shown that the proposed model can help chicken farmers to deal with the problems of chicken-henhouse assignment, chicken raising and harvesting, and may thus contribute to increasing profits. A case study of a chicken farmer in Yunlin County (Taiwan) was carried out to illustrate the application of the proposed model. Sensitivity analysis was also conducted to explore the influence of parameter variations.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jun Bi ◽  
Zhen Wu ◽  
Lei Wang ◽  
Dongfan Xie ◽  
Xiaomei Zhao

An airport gate is the core resource of an airport operation, which is an important place for passengers to get on and off the aircraft and for maintaining aircraft. It is the prerequisite for other related dispatch. Effective and reasonable allocation of gates can reduce airport operating costs and increase passenger satisfaction. Therefore, an airport gate assignment problem (AGAP) needs to be urgently solved in the actual operation of the airport. In this paper, considering the actual operation of the airport, we formulate an integer programming model for AGAP by considering multiple constraints. The model aims to maximize the number of passengers on flights parked at the gate. A tabu search-based algorithm is designed to solve the problem. In the process of algorithm design, an effective initial solution is obtained. A unique neighborhood structure and search strategy for tabu search are designed. The algorithm can adapt to the dynamic scheduling of airports. Finally, tests are performed using actual airport data selected from Kunming Changshui International Airport in China. The experimental results indicate that the proposed method can enhance the local search ability and global search ability and get satisfactory results in a limited time. These results provide an effective support for the actual gate assignment in airport operations.


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