The 6-month progress report summarizes work completed on the author's Ph.D. research from July 2022 to December 2022. The objectives of the research are to optimize scheduling for flexible manufacturing systems using soft computing techniques. Two papers were published in peer-reviewed journals during this period. The next steps are to submit the Ph.D. thesis by the next six-month period. The research involves developing novel hybrid algorithms to minimize objectives like makespan and workload for flexible job shop scheduling problems.

1. Six Month Progress Report Presentation
for period of
July 2022- December 2022
By Under the guidance of
Gayathri Devi K Prof RS Mishra & Prof AK Madan
2k16/Phd/ME/61

2. Objective(s) of Ph.D. research work.
The main objective is to optimize scheduling for FMS by Soft Computing Techniques
This study aims to solve scheduling problem for three types
a) FJSP b) FMS set up c) Real-Life Case study
• Solve multi-objective scheduling of FJSP for numerous benchmark instances with the following objectives to
minimize
1) The maximum completion time of machines or jobs makespan (MSmax).
2) Maximum machine workload (WLmax), i.e., the maximum processing time of a machine.
3) The total workload of machines, i.e., total processing time over all machines (WLtotal).
4) Total idle time, i.e., idle time of machines (Tidle ).
5) Total tardiness, i.e., lateness of jobs (Tlate ).

3.  Minimize the machine idle time and the total penalty cost by a combined
objective function (COF) for an FMS setup.
 Obtain an optimized schedule with an objective to minimize makespan,
maximum machine workload and total workload for a case study conducted in an
Oil Blending Plant in Faridabad.
 To develop three novel hybrid algorithms 1) GAPSOTS (Hybridization of GA,
PSO, TS) 2) HAdFA (Hybrid Adaptive Firefly Algorithm- FA with adaptive
features hybridized with Simulated Annealing-SA) 3) HFPA (Hybrid Flower
Pollination Algorithm which is the hybridization of the Flower Pollination
Algorithm with SA for solving the aforementioned objectives.

4.  Study the impact of adaptive parameters in FA and compare it with FPA without
adaptive parameters. Very few papers have used adaptive parameters in SI. To the
best of our knowledge, none of the articles in FA, have incorporated adaptive
features with FA for scheduling problems. Based on these observations, we have
integrated adaptive parameters in FA and we have hybridized SA with FA and
FPA.
 Do a performance comparison of proposed techniques with other recent meta-
heuristics to demonstrate the efficiency of HAdFA, GAPSOTS and HFPA.
 The simulation was done on 63 well-known benchmark problems of FJSP, an
FMS setup and a real-life case study.

5. Objective(s) to be completed during this
Progress Report Period
•To publish SCI papers
•To do pre-phd presentation.
•To submit thesis

6. Work/ Objective(s) completed during progress
report period
•Published a paper in SCI journal
•Published one paper in International Journal.
•Applied for pre-phd presentation.

7. Objective(s) next six months
•To submit Thesis

8. Publications during July 2022- Dec 2022
• Paper titled "Integrated Approach of Scheduling a Flexible Job Shop using
Enhanced Firefly and Hybrid Flower Pollination Algorithms" has been published
in International Journal of Industrial Engineering: Theory, Applications, and Practice,
Vol 29, Issue-6, 2022
• Paper titled, “A Comprehensive Review of Recent Variants and Modifications of
Firefly Algorithm” has been published in International Journal of Engineering and
Management Research., Volume 12, Issue -6, 2022.
• Another paper titled "An Improved Hybrid Flower Pollination Algorithm for
Energy Cognizant Flexible Job shop Scheduling Problem" is under review in Facta
Universatis, series, Mechanical Engineering.