Open AccessFirefly Algorithm: Minimizing Cost on Single-Level Lot-Sizing Problem
Author(s) -
Siti Hafawati Jamaluddin,
Nurul Azleeka Zulkipli,
Norwaziah Mahmud,
Nur Syuhada Muhamat Pazil
Publication year - 2018
Publication title -
journal of computing research and innovation
Language(s) - English
Resource type - Journals
ISSN - 2600-8793
DOI - 10.24191/jcrinn.v3i1.89
Subject(s) - sizing , firefly algorithm , production (economics) , total cost , mathematical optimization , production cost , computer science , holding cost , time horizon , matlab , algorithm , mathematics , engineering , economics , particle swarm optimization , mechanical engineering , art , visual arts , macroeconomics , microeconomics , operating system
Nowadays, the industrial company plays a very important role to our country. However, the manufacturer industry has big issues in the production planning which called planning horizon where, the lot-sizing problem is one of the most important issues in the production planning area. In lot-sizing problem, the manufacturers are facing the problems in determining the setup cost when there is no consistency and efficiency in organizing the production plan. From the problem emerge, the minimum of production cost is determined by using firefly algorithm. From the minimum production cost obtained, the optimal setup cost on single-level lot-sizing problem is defined. In this study, the result is obtained by using MATLAB R2017a software to minimize the production cost on single-level lot-sizing problem where the minimum production cost is are for one month is $154 while, the minimum production cost for 12 months is $1760.89. From those minimum total cost obtained by using firefly algorithm, the optimal setup cost for one month is $86.83 while optimal setup cost for 12 months are $86.51, $86.81, $88.30, $95.39, $112.01, $102.92, $93.30, $85.90, $106.50, $85.77, $99.46 and $115.30 respectively. As a conclusion, firefly algorithm is applicable to use in minimizing production cost on single-level lot-sizing problem since the result obtained gives the better solution compared to the exact solution