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All Journal Journal of Intelligent Decision Support System (IDSS) Jurnal Mandiri IT
Ruri Hartika Zain
Universitas Putra Indonesia YPTK Padang, Indonesia
Computer Science & IT Library & Information Science Mathematics

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A mixed integer linear programming approach for last-mile e-commerce optimization through micro-fulfillment centers Fristi Riandari; Ruri Hartika Zain
Journal of Intelligent Decision Support System (IDSS) Vol 9 No 1 (2026): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v9i1.338

Abstract

The rapid growth of e-commerce increases the complexity of last-mile delivery due to high distribution costs, urban congestion, and increasingly tight delivery time demands. This study proposes a Mixed Integer Linear Programming (MILP) approach to optimize e-commerce last-mile distribution through the determination of Micro-Fulfillment Centers (MFCs). The model simultaneously determines (i) the locations of candidate MFCs to be opened and (ii) the allocation of demand zones to selected facilities, with the objective of minimizing the total network cost consisting of fixed facility costs and variable last-mile service costs. Service quality is enforced through a hard service level agreement (SLA) mechanism by limiting allocation to only pairs of facility zones that meet a certain travel time threshold, while operational feasibility is guaranteed through capacity constraints at each MFC. The model outputs are implementable in the form of selected MFC locations, zone allocation maps, and performance indicators for evaluation, including total cost decomposition, weighted travel time metrics, and facility capacity utilization to identify potential bottlenecks. Numerical illustrations show that the MILP formulation yields feasible location–allocation decisions with respect to SLA and capacity, while avoiding the “closest/fastest” heuristic that can potentially lead to facility overload. This framework supports decision-makers in designing efficient, responsive, and scalable last-mile networks, and can be extended to incorporate demand uncertainty, SLA penalties (soft-SLAs), multi-echelon structures, and sustainability objectives.
Minimize shipping costs from multi-warehouse to multi-outlet with VAM and MODI Fristi Riandari; Ruri Hartika Zain
Jurnal Mandiri IT Vol. 14 No. 3 (2026): Jan: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i3.506

Abstract

Distribution costs are a dominant component in logistics operations, especially in multi-warehouse to multi-outlet delivery schemes involving variations in supply capacity, demand, and route costs. This study aims to minimize shipping costs by modeling the problem as a Transportation Problem (TP), generating an initial solution using Vogel's Approximation Method (VAM), and ensuring an optimal solution using the Modified Distribution Method (MODI). The case study was conducted in one planning period with input data in the form of a matrix of shipping costs per unit, supply capacity per warehouse, and demand per outlet (balanced condition). The results show that the baseline distribution cost is 4,898 (thousand IDR), while the initial VAM solution reduces the cost to 3,777 (thousand IDR). After optimality testing and improvements using MODI, the minimum cost is 3,605 (thousand IDR), with an additional improvement of 172 (thousand IDR) from the VAM solution. Compared to the baseline, the optimal solution provides savings of 1,293 (thousand IDR) or 26.40%, without violating the supply-demand constraint. These findings confirm that the VAM-MODI flow is effective as a fast, audit-friendly, and applicable end-to-end procedure for the preparation of minimum cost delivery plans in logistics companies.
Co-Authors Fristi Riandari