Journal of Combinatorial Optimization

The balanced traveling salesman problem (BTSP) is a variant of the traveling salesman problem, in which one seeks a tour that minimizes the difference between the largest and smallest edge costs in the tour. The BTSP, which is obviously NP-hard, ...

Edge disjoint paths have a closed relationship with edge connectivity and are anticipated to garner increased attention in the study of the reliability and edge fault tolerance of a readily scalable interconnection network. Note that this ...${}_{}$${}_{}{}_{\mathrm{}}^{}$${\mathrm{}}^{}\mathrm{}$$\mathrm{}$$\mathrm{}$$\mathrm{}\frac{}{\mathrm{}}\mathrm{}{\mathrm{}}^{\frac{}{\mathrm{}}}$${\mathrm{}}^{\frac{}{\mathrm{}}}\frac{{\mathrm{}}^{\mathrm{}}\mathrm{}{\mathrm{}}^{\mathrm{}}}{\mathrm{}}{\mathrm{}}^{\frac{}{\mathrm{}}}$$\mathrm{}\mathrm{}\frac{}{\mathrm{}}\mathrm{}$$\mathrm{}\mathrm{}\mathrm{}\mathrm{}$$\frac{}{\mathrm{}}\mathrm{}$$\mathrm{}\mathrm{}$

This paper proposes a novel Inventory-Location problem that integrates supplier selection decisions to design a three-echelon supply chain network, under a continuous (s,Q) inventory control policy at the warehouses. In this problem, a set of ...

To solve the problem of predicting water level in front of check gate under different time scales, a different time scale prediction model with a long short term memory (LSTM) neural network based on adaptive inertia weight comprehensive learning ...

Shuffled Frog leaping algorithm (SFLA) is a multi population swarm intelligence algorithm which employs population partitioning techniques during the evolutionary stage. Methods adopted by SFLA for partitioning the population into memeplexes play ...

The packing number of a signed graph $(G,\sigma )$, denoted $\rho (G,\sigma )$, is the maximum number l of signatures ${\sigma }_1,{\sigma }_2,\dots ,{\sigma }_l$ such that each ${\sigma }_i$ is switching equivalent to $\sigma$ and the sets of negative edges $E_{{\sigma }_i}^{-}$ of $(G,{\sigma }_i)$ are pairwise disjoint. A signed graph packs ...

We study a generalization of the classical Hamiltonian path problem, where multiple salesmen are positioned at the same depot, of which no more than k can be selected to service n destinations, with the objective to minimize the total travel ...$\mathrm{}\mathrm{}\mathrm{}$${}^{\mathrm{}}$$\mathrm{}$

Given a graph G with a terminal set $R\subseteq V(G)$, the Steiner tree problem (STREE) asks for a set $S\subseteq V(G)\backslash R$ such that the graph induced on $S\cup R$ is connected. A split graph is a graph which can be partitioned into a clique and an independent set. It is ...$\mathrm{}\mathrm{}{}^{\mathrm{}}$

This work is to discuss the fault-tolerant facility location problem with submodular penalties. We propose an LP-rounding 2.27-approximation algorithm, where every demand point j has a requirement that $t_j$ distinct facilities serve it. This is the ...

It is well-known that the classical Johnson’s Rule leads to optimal schedules on a two-stage flowshop. However, it is still unclear how Johnson’s Rule would help in approximation algorithms for scheduling an arbitrary number of parallel two-stage ...$$

We consider the non-preemptive scheduling problem on identical machines where there is a parameter B and each machine in every unit length time interval can process up to B different jobs. The goal function we consider is the makespan minimization ...

This paper introduces an integer linear program for a variant of the linear ordering problem. This considers, besides the pairwise preferences in the objective function as the linear ordering problem, positional preferences (weighted rank) in the ...

Identifying certain conditions that ensure the Hamiltonicity of graphs is highly important and valuable due to the fact that determining whether a graph is Hamiltonian is an NP-complete problem.For a graph G with vertex set V(G) and edge set E(G), ...${}_{\mathrm{}}$${}_{\mathrm{}}$${}_{\mathrm{}}\underset{{}_{}{}_{}}{}{}_{}{}_{}{}_{}{}_{}$${}_{\mathrm{}}\underset{{}_{}{}_{}}{}{}_{}{}_{}{}_{}{}_{}$${}_{}{}_{}$${}_{}$$\mathrm{}$$\mathrm{}{}_{\mathrm{}}{}_{\mathrm{}}$$\mathrm{}$