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A Hybrid Greedy Algorithm and Simulated Annealing for Single Container Loading Problem: A Case Study Gede A Widyadana; Audrey Tedja Widjaja; Kun Jen Wang
Jurnal Teknik Industri Vol. 20 No. 2 (2018): December 2018
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (609.487 KB) | DOI: 10.9744/jti.20.2.89-94

Abstract

A single container loading problem is a problem to effectively load boxes in a three-dimensional container. There are many researchers in this problem try to find the best solution to solve the problem with feasible computation time and to develop some models to solve real case problem. Heuristics are the most method used to solve this problem since the problem is an NP-hard. In this paper, we introduce a hybrid greedy algorithm and simulate annealing algorithm to solve a real container loading problem in one flexible packaging company in Indonesia. Validation is used to show that the method can be applied practically. We use seven real cases to check the validity and performance of the model. The proposed method outperformed the solution developed by the company in all seven cases with feasible computational time.
Optimal Deteriorating Inventory Models for Varies Supply Life Cycles Gede A Widyadana; Kun Jen Wang; Nyoman Sutapa
International Journal of Supply Chain Management Vol 9, No 3 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (534.989 KB)

Abstract

Agriculture items, such as fruits and vegetables, have different supply and demand characteristics during a harvest period. Fruits supply in the first and end of harvest time are not reliable so sometimes supply are not available when needed. Fruits demand is different during harvest season. In the first harvest season, demand depends on price and at the end of harvest time, the demand depends on presentation of the items. In this study, inventory deteriorating items models for the first and the end of the harvest season are developed. Since closed-form solutions cannot be derived from the models, a Genetic Algorithm and a heuristic method are used to solve the problems. A numerical example and sensitivity analysis are conducted to illustrate the model and get insights. The sensitivity analysis shows that the supplier will increase his price when supply is not reliable at the early harvest period.  The results show that the unreliable supply is susceptible to the total cost at the end of the harvest period.