LAPSE:2026.0497
Published Article

LAPSE:2026.0497
A novel decomposition-based approach to solve heterogeneous capacitated vehicle routing problems
June 12, 2026
Abstract
The Heterogeneous Capacitated Vehicle Routing Problem (HCVRP) is a fundamental extension of the classical Vehicle Routing Problem in which customer demands must be satisfied using a fleet of vehicles with varying capacities and costs. In this paper, a novel and intuitive decomposition-based formulation for HCVRP is presented that decomposes the problem into two tractable subproblems: (i) a route generation and an optimal customer sequencing problem and (ii) a vehicle route assignment problem. In the first stage, all feasible customer combinations are constructed as routes, and for each route an optimization problem is solved to identify the optimal customer sequence that results in the minimum distance travelled. In the second stage, the optimal routes are selected, and vehicles are assigned using a mixed integer linear programming (MILP) formulation that minimizes the fixed cost of vehicle utilisation and total transportation costs, ensuring demand satisfaction for all customers while meeting vehicle capacity limitations. Computational results demonstrate that the decomposition strategy preserves optimality while significantly reducing solution time.
The Heterogeneous Capacitated Vehicle Routing Problem (HCVRP) is a fundamental extension of the classical Vehicle Routing Problem in which customer demands must be satisfied using a fleet of vehicles with varying capacities and costs. In this paper, a novel and intuitive decomposition-based formulation for HCVRP is presented that decomposes the problem into two tractable subproblems: (i) a route generation and an optimal customer sequencing problem and (ii) a vehicle route assignment problem. In the first stage, all feasible customer combinations are constructed as routes, and for each route an optimization problem is solved to identify the optimal customer sequence that results in the minimum distance travelled. In the second stage, the optimal routes are selected, and vehicles are assigned using a mixed integer linear programming (MILP) formulation that minimizes the fixed cost of vehicle utilisation and total transportation costs, ensuring demand satisfaction for all customers while meeting vehicle capacity limitations. Computational results demonstrate that the decomposition strategy preserves optimality while significantly reducing solution time.
Record ID
Keywords
Decomposition, Mixed integer linear programming, Optimization, Vehicle Routing
Subject
Suggested Citation
Krishna VV, Kapadi M, Verma P, Misra S. A novel decomposition-based approach to solve heterogeneous capacitated vehicle routing problems. Systems and Control Transactions 5:2355-2361 (2026) https://doi.org/10.69997/sct.157285
Author Affiliations
Krishna VV: Department of Chemical engineering, Indian Institute of Technology Tirupati, Andhra Pradesh, India - 517609 [ORCID]
Kapadi M: Linde South Asia Services Limited, Pune, Maharashtra, India - 411045
Verma P: Linde South Asia Services Limited, Pune, Maharashtra, India - 411045
Misra S: Department of Chemical engineering, Indian Institute of Technology Tirupati, Andhra Pradesh, India - 517609 [ORCID]
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Kapadi M: Linde South Asia Services Limited, Pune, Maharashtra, India - 411045
Verma P: Linde South Asia Services Limited, Pune, Maharashtra, India - 411045
Misra S: Department of Chemical engineering, Indian Institute of Technology Tirupati, Andhra Pradesh, India - 517609 [ORCID]
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Journal Name
Systems and Control Transactions
Volume
5
First Page
2355
Last Page
2361
Year
2026
Publication Date
2026-06-12
Version Comments
Original Submission
Other Meta
PII: 2355-2361-657-SCT-5-2026, Publication Type: Journal Article
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LAPSE:2026.0497
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https://doi.org/10.69997/sct.157285
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