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2 2020

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Retraction: Clusters analysis application on transportation network

Jayarathna Nuwan Dhammika, Jayawardene Chula J .

Journal of Sustainable Development of Transport and Logistics

2020

Vol. 5, No. 1

28--36

The government of Sri Lanka established several economic centres in the provinces according to the budget proposals in the year 1998. The Dambulla economic centre was the first such centre that was established on the 01st of April 1999. Thereafter, a number of economic centres were established throughout the island. However, the Dambulla main hub remained the central warehouse of vegetables in the island. This paper deals with a vehicle scheduling problem related to transportation, and investigates a method whereby a solution can be arrived at to overcome the problem using linear programming (LP). Marketing Department Logistics (MDL) Ltd needs to distribute vegetables and fruits to different provinces. Its main hub is situated near the Dambulla vegetable and fruit market, and minor hubs are situated in different provinces in Sri Lanka. The main objective of this research is building a cost minimized model which creates a suitable method for delivering vegetables and fruits from the Dambulla major hub through its minor hubs to outlets in the provinces. Hence, to optimize the cost of outbound distribution, a mathematical model has been developed by using Integer Linear Programming, and by using reliable sources to collect data. Software assistance was obtained using the LINGO 06 optimizer, Java, MS Access and MS Excel tools to solve this mathematical model. This study is based on the Dambulla economic centre. This is an initial step to bring a correct protocol to arrange a transport model to distribute the vegetables and fruits from this centre in a cost-effective way. According to this study, all districts in Sri Lanka could be divided into four clusters. At the beginning of this research, we assumed that each district contains two warehouses and three vendors. This model is flexible enough to be re-scheduled at any request. It paves the way to create a larger model for solving any type of transportation planning problem.

Cut Order Planning Optimisation in the Apparel Industry

Ünal Can, Yüksel Alime Dere

Fibres & Textiles in Eastern Europe

2020

Vol. 28, no. 1 (139)

8--13

Nowadays, apparel businesses have to cut down on their costs in order to ensure the continuity of their activities and to expand them. Fabric costs cover about 50-60% of production costs. In this study, for the minimisation of fabric costs, the cutting department in enterprises was investigated and the cut order plans developed by mixed integer nonlinear programming. Examples were taken from the enterprises that were implemented. A mathematical model was then developed to be used in mixed integer nonlinear programming for a manual cut order plan, and a program code was created in LINGO optimisation software. With the program code developed, optimum results that cannot be manually calculated by an operator is obtained. The amounts of fabric to be used as a result of the cut order plan were applied to the samples taken from the enterprises, and the manual solution and model developed were compared. As a result of the comparisons made, thanks to the model, fabric developed, usage is reduced and fabric cost minimisation ensured.

Obecnie firmy odzieżowe muszą obniżać koszty, aby zapewnić ciągłość swoich działań i stale je rozwijać. Koszty zakupu tkanin stanowią około 50-60% kosztów produkcji. W badaniu, w celu zminimalizowania kosztów tkanin, zbadano działy cięcia (krojownie) w przedsiębiorstwach i opracowano plany zamówień cięcia przez mieszane nieliniowe programowanie całkowitoliczbowe. Następnie opracowano model matematyczny do zastosowania w programowaniu nieliniowym o mieszanych liczbach całkowitych do ręcznego planu zamówienia cięcia, a kod oprogramowania został utworzony w oprogramowaniu optymalizacyjnym LINGO. Po opracowaniu kodu programu uzyskano optymalne wyniki, których operator nie może ręcznie obliczyć. Ilości tkanin, które mają zostać użyte w wyniku planu zamówienia cięcia, zastosowano do próbek pobranych z przedsiębiorstw i porównano opracowane ręczne rozwiązanie i model. W wyniku dokonanych porównań i dzięki opracowanemu modelowi ograniczono zużycie i zapewniono minimalizacja kosztów zakupu tkaniny.