Penjadwalan Flwoshop untuk Mengurangi Total Tardiness Cost dan Total Overtime Cost pada Produksi Reinforcement Bar dan Footplate Menggunakan Metode Mixed Integer Programming

UD Bagus Nanang Jaya (BNJ) merupakan perusahaan manufaktur dalam bidang bahan konstruksi yang memproduksi reinforcement bar dan footplate. Terdapat 4 produk yang dikerjakan pada 3 stage dalam model produksi flowshop. Saat ini BNJ menjadwalkan produksinya bedasarkan prinsip first come first served dan belum memiliki penjadwalan pasti. Model penjadwalan saat ini mengakibatkan adanya keterlambatan produksi serta menghasilkan tardiness cost dan overtime cost yang harus dikeluarkan. Oleh karena itu, penelitian ini bertujuan melakukan penjadwalan dengan kriteria performansi berupa minimasi total tardiness cost dan total overtime cost. Pada penelitian ini, permasalahan penjadwalan diselesaikan menggunakan mixed integer programming (MIP) dengan fungsi tujuan berupa minimasi total tardiness cost dan total overtime cost. Berdasarkan penjadwalan yang telah dibangun menggunakan MIP, hasil menunjukkan bahwa terdapat penurunan tardiness cost dari Rp. 432.588,00 menjadi Rp. 0,00 atau sebesar 100% dari penjadwalan awal. Penurunan juga terjadi pada overtime cost dimana berkurang dari Rp. 488.666,00 menjadi Rp. 436.267,00 atau 10.72% dari penjadwalan awal. Pengujian model dilakukan untuk mengetahui perubahan hasil penjadwalan berdasarkan perubahan parameter. Hasil simulasi menunjukkan adanya persamaaan nilai tardiness cost yang dihasilkan sedangkan overtime cost berubah. Hal tersebut menunjukkan bahwa perubahan jumlah job dan jumlah unit yang diproduksi tidak mempengaruhi nilai tardiness cost namun berpengaruh pada nilai overtime cost. Kemudian berdasarkan penjelasan tersebut dapat disimpulkan bahwa model yang dibangun mampu menyelesaikan permasalahan keterlambatan yang dialami perusahaan dan menghasilkan penjadwalan yang lebih baik dari penjadwalan awal

An effective hybrid ant lion algorithm to minimize mean tardiness on permutation flow shop scheduling problem

This article aimed to develop an improved Ant Lion algorithm. The objective function was to minimize the mean tardiness on the flow shop scheduling problem with a focus on the permutation flow shop problem (PFSP). The Hybrid Ant Lion Optimization Algorithm (HALO) with local strategy was proposed, and from the total search of the agent, the NEH-EDD algorithm was applied. Moreover, the diversity of the nominee schedule was improved through the use of swap mutation, flip, and slide to determine the best solution in each iteration. Finally, the HALO was compared with some algorithms, while some numerical experiments were used to show the performances of the proposed algorithms. It is important to note that comparative analysis has been previously conducted using the nine variations of the PFSSP problem, and the HALO obtained was compared to other algorithms based on numerical experiments

Hybrid genetic algorithm based on bin packing strategy for the unrelated parallel workgroup scheduling problem

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In this paper we focus on an unrelated parallel workgroup scheduling problem where each workgroup is composed of a number of personnel with similar work skills which has eligibility and human resource constraints. The most difference from the general unrelated parallel machine scheduling with resource constraints is that one workgroup can process multiple jobs at a time as long as the resources are available, which means that a feasible scheduling scheme is impossible to get if we consider the processing sequence of jobs only in time dimension. We construct this problem as an integer programming model with the objective of minimizing makespan. As it is incapable to get the optimal solution in the acceptable time for the presented model by exact algorithm, meta-heuristic is considered to design. A pure genetic algorithm based on special coding design is proposed firstly. Then a hybrid genetic algorithm based on bin packing strategy is further developed by the consideration of transforming the single workgroup scheduling to a strip-packing problem. Finally, the proposed algorithms, together with exact approach, are tested at different size of instances. Results demonstrate that the proposed hybrid genetic algorithm shows the effective performance

Matheuristic algorithms for minimizing total tardiness in the m-machine flow-shop scheduling problem

International audienc