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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi
Mohamad Muslikh
Brawijaya University
Mathematics

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A Hybrid Sweep-Nearest Neighbor-Tabu Search Approach for CVRP in FMCG Route Distribution Sikhatun Naimah Evary; Sobri Abusini; Mohamad Muslikh
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.35953

Abstract

This study addresses the Capacitated Vehicle Routing Problem (CVRP) in the distribution of Fast-Moving Consumer Goods (FMCG) by proposing a hybrid approach that combines the Sweep algorithm, Nearest Neighbor (NN) method, and Tabu Search (TS) algorithm. The objective is to satisfy consumer demand and vehicle capacity restrictions while minimizing the overall journey distance. The Sweep algorithm is used to cluster customers based on polar coordinates, the NN method determines initial delivery routes within each cluster, and TS refines those routes to find near-optimal solutions. Implemented on a real-world dataset of 248 stores in Malang, the proposed hybrid method achieved significant reductions in the number of clusters and total travel distance compared to conventional approaches. Results show that the Sweep algorithm successfully reduced the number of delivery clusters from 26 to 18, achieving a 30.77% reduction in grouping efficiency. Using the Nearest Neighbor method, the total route distance was 2,191.08 km. Further optimization with Tabu Search reduced the Distance to 2141.31 km. Compared to the conventional method, which is 2345.90 km, the hybrid approach resulted in an 8.72% improvement in route efficiency. These findings demonstrate that the integrated method is effective for large-scale distribution problems under capacity constraints. The hybrid method offers a practical and computationally efficient solution for large-scale FMCG distribution networks.
Adaptive Portfolio Rebalancing for NASDAQ-100 Stocks with Hippopotamus Optimization Algorithm under Transaction Costs Safrizal Ardana Ardiyansa; Mohamad Muslikh; Syaiful Anam
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 2 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i2.43876

Abstract

This study proposes a transaction cost-aware portfolio optimization framework for NASDAQ-100 stocks based on the Hippopotamus Optimization Algorithm (HOA). The mathematical model extends the classical mean-variance framework by incorporating transaction costs into a Net Sharpe Ratio (NSR) objective function. Daily adjusted closing prices of NASDAQ-100 constituent stocks from 2021 to 2025 are employed, with the twenty highest-ranked stocks according to the Sharpe Ratio (SR) selected as the candidate investment universe. Each optimization experiment is independently repeated 25 times to evaluate robustness and solution stability. The results indicate that the proposed HOA consistently achieves competitive optimization performance with very small variability across repeated runs throughout the investment horizon. Although several competing algorithms attain comparable or slightly better objective values during particular rebalancing periods, HOA remains among the strongest-performing methods while exhibiting stable convergence behavior. Throughout the investment horizon, the proposed algorithm produces the highest average cumulative portfolio value of \$5,307.87 \$125.71 from an initial investment of \$1,000, corresponding to an average annual return of 40.03% 0.68%, together with the highest average SR and NSR of 1.5736 0.0151, while maintaining competitive maximum drawdown and transaction costs. These findings demonstrate that incorporating transaction costs directly into the optimization objective enables HOA to achieve a favorable balance between portfolio growth, risk-adjusted performance, and trading efficiency under dynamic market conditions.
Co-Authors Anam, Syaiful Safrizal Ardana Ardiyansa Sikhatun Naimah Evary Sobri Abusini