TY - GEN
T1 - Complexity and Approximation Algorithms for Fixed Charge Transportation Problems
AU - Chen, Yong
AU - Li, Shi
AU - Liang, Zihao
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026
Y1 - 2026
N2 - The Fixed Charge Transportation (FCT) problem models transportation scenarios where we need to send a commodity from n sources to m sinks, and the cost of sending a commodity from a source to a sink consists of a linear component and a fixed component. Despite extensive research on exponential time exact algorithms and heuristic algorithms for FCT and its variants, their approximability and computational complexity are not well understood. In this work, we initiate a systematic study of the approximability and complexity of these problems. When there are no linear costs, we call the problem the Pure Fixed Charge Transportation (PFCT) problem. We also distinguish between cases with general, sink-independent, and uniform fixed costs; we use the suffixes “-S” and “-U” to denote the latter two cases, respectively. This gives us six variants of the FCT problem. We give a complete characterization of the existence of O(1)-approximation algorithms for these variants. In particular, we give 2-approximation algorithms for FCT-U and PFCT-S, and a (6/5+ϵ)-approximation for PFCT-U. On the negative side, we prove that FCT and PFCT are NP-hard to approximate within a factor of O(log2-ϵ(max{n,m})) for any constant ϵ>0, FCT-S is NP-hard to approximate within a factor of clog(max{n,m}) for some constant c>0, and PFCT-U is APX-hard. Additionally, we design an Efficient Parameterized Approximation Scheme (EPAS) for PFCT when parameterized by the number n of sources, and an O(1/ϵ)-bicriteria approximation for the FCT problem, when we are allowed to violate the demand constraints for sinks by a factor of 1±ϵ.
AB - The Fixed Charge Transportation (FCT) problem models transportation scenarios where we need to send a commodity from n sources to m sinks, and the cost of sending a commodity from a source to a sink consists of a linear component and a fixed component. Despite extensive research on exponential time exact algorithms and heuristic algorithms for FCT and its variants, their approximability and computational complexity are not well understood. In this work, we initiate a systematic study of the approximability and complexity of these problems. When there are no linear costs, we call the problem the Pure Fixed Charge Transportation (PFCT) problem. We also distinguish between cases with general, sink-independent, and uniform fixed costs; we use the suffixes “-S” and “-U” to denote the latter two cases, respectively. This gives us six variants of the FCT problem. We give a complete characterization of the existence of O(1)-approximation algorithms for these variants. In particular, we give 2-approximation algorithms for FCT-U and PFCT-S, and a (6/5+ϵ)-approximation for PFCT-U. On the negative side, we prove that FCT and PFCT are NP-hard to approximate within a factor of O(log2-ϵ(max{n,m})) for any constant ϵ>0, FCT-S is NP-hard to approximate within a factor of clog(max{n,m}) for some constant c>0, and PFCT-U is APX-hard. Additionally, we design an Efficient Parameterized Approximation Scheme (EPAS) for PFCT when parameterized by the number n of sources, and an O(1/ϵ)-bicriteria approximation for the FCT problem, when we are allowed to violate the demand constraints for sinks by a factor of 1±ϵ.
KW - Approximation Algorithm
KW - Complexity
KW - Fixed Charge Transportation problem
UR - https://www.scopus.com/pages/publications/105028248505
U2 - 10.1007/978-981-95-4839-2_1
DO - 10.1007/978-981-95-4839-2_1
M3 - Conference contribution
AN - SCOPUS:105028248505
SN - 9789819548385
T3 - Lecture Notes in Computer Science
SP - 3
EP - 14
BT - Theory and Applications of Models of Computation - 19th Annual Conference, TAMC 2025, Proceedings
A2 - Li, Min
A2 - Xia, Mingji
A2 - Zhang, Peng
PB - Springer Science and Business Media Deutschland GmbH
T2 - 19th Annual Conference on Theory and Applications of Models of Computation, TAMC 2025
Y2 - 19 September 2025 through 21 September 2025
ER -