This paper investigates the superposition problem of two or more individual semi-Markov decision processes (SMDPs). The new sequential decision process superposed by individual SMDPs is no longer an SMDP and cannot be handled by routine iterative algorithms, but we can expand its state spaces to obtain a hybrid-state SMDP. Using this hybrid-state SMDP as an auxiliary and inspired by the Robbins–Monro

Sustainable scheduling is getting more and more attention with economic globalization and sustainable manufacturing. However, fewer studies on the batch scheduling problem consider energy consumption. This paper conducts an investigation into the multi-objective hybrid flow shop batch-scheduling problem with the objectives of minimizing both the makespan and electrical energy consumption. The study

The Euclidean Steiner problem is the problem of finding a set \(\mathcal{S}\mathcal{t}\), with the shortest length, such that \(\mathcal{S}\mathcal{t}\cup \mathcal {A}\) is connected, where \(\mathcal {A}\) is a given set in a Euclidean space. The solutions \(\mathcal{S}\mathcal{t}\) to the Steiner problem will be called Steiner sets while the set \(\mathcal {A}\) will be called input. Since every

This paper studies the inefficiency of multiplicative approximate Nash Equilibrium for scheduling games. There is a set of machines and a set of jobs. Each job could choose one machine and be processed by the chosen one. A schedule is a \(\theta \)-NE if no player has the incentive to deviate so that it decreases its cost by a factor larger than \(1+\theta \). The \(\theta \)-NE is a generation of

In this paper, we investigate the data mule scheduling with handling time and time span constraints (DMSTC) in which the goal is to minimize the number of data mules dispatched from a depot that are used to serve target sensors located on a wireless sensor network. Each target sensor is associated with a handling time and each dispatched data mule must return to the original depot before time span

In the production scheduling of prefabricated components, a scheduling model considering the learning effect of processing time and the deterioration effect of delivery time in this paper is provided. More precisely, it asks for an assignment of a series of independent prefabricated jobs that arrived over time to a single machine for processing, and once the execution of a job is finished, it will

Let F(G) and \(F_t(G)\) be the zero forcing number and the total forcing number of a graph G, respectively. In this paper, we study the relationship between the total forcing number of a graph and its vertex covering number (or independence number), and prove that \(F_t(G) \le \Delta \alpha (G)\) and \(F_t(G) \le (\Delta - 1)\beta (G) + 1\) for any connected graph G with the maximum degree \(\Delta

Desktop cloud technology has revolutionized modern computing by enabling remote desktop functionality through cloud computing and virtualization. However, traditional fuzzy set theories struggle with the uncertainties inherent in these environments. This study addresses this gap by introducing the probabilistic p, q-rung orthopair fuzzy model, a novel extension that integrates probabilistic elements

Cloud computing has a powerful capability to handle a large number of tasks. However, this capability comes with significant energy requirements. It is critical to overcome the challenge of minimizing energy consumption within cloud service platforms without compromising service quality. In this paper, we propose a heuristic energy-saving scheduling algorithm, called Real-time Multi-workflow Energy-efficient

Consider a simple (edge weighted) graph \(G = \left( {V,E} \right)\) with \(\left| V \right| = n\) and \(\left| E \right| = m\). Let \(xy \in E\). The domination of a vertex \(z \in V\) by an edge \(xy\) is defined as \(z\) belonging to the closed neighborhood of either \(x\) or \(y\). An edge set \(W\) is considered as an edge-vertex dominating set of \(G\) if each vertex of \(V\) is dominated by

Determining the minimum genus of a graph is a fundamental optimisation problem in the study of network design and implementation as it gives a measure of non-planarity of graphs. In this paper, we are concerned with determining the smallest value of g such that a given graph G has an embedding on the orientable surface of genus g. In particular, we consider the Cartesian product of graphs since this

In this paper we study a scheduling problem with release dates and submodular rejection penalties on multiple (parallel) identical serial-batch machines. For this problem, each machine processes jobs in batches, jobs in a common batch start and finish simultaneously, and the duration of a batch is equal to the sum of a setup time and the total processing time of jobs in it. Some jobs are accepted and

Consider a set of items, X, with a total of n items, among which a subset, denoted as \(I\subseteq X\), consists of defective items. In the context of group testing, a test is conducted on a subset of items Q, where \(Q \subset X\). The result of this test is positive, yielding 1, if Q includes at least one defective item, that is if \(Q \cap I \ne \emptyset \). It is negative, yielding 0, if no defective

In this paper, a reduced quadratic surface support vector machine (RQSSVM) classification model is proposed and solved using the augmented Lagrange method. The new model can effectively handle nonlinearly separable data without kernel function selection and parameter tuning due to its quadratic surface segmentation facility. Meanwhile, the maximum margin term is replaced by an \(L_2\) regularization

In this paper, intuitionistic fuzzy multi-objective linear fractional programming problems (IFMOLFPs) with several fractional criteria, including profit/cost, profit/time, or profitability ratio maximization, are considered. Moreover, all parameters, with the exception of the decision variables, are characterized as triangular intuitionistic fuzzy numbers. The component-wise optimization method is

The performance of machine learning algorithms is significantly influenced by the quality of the underlying dataset, which often comprises a mix of essential and redundant features. Feature selection, which identifies and discards these redundant features, plays a pivotal role in reducing computational and storage overheads. Current methodologies for this task primarily span filter-based and wrapper-based

Solving the optimal order quantity for products with stock-dependent demand is a challenging task as both exact values of multiple parameters and complicated procedures are required. Motivated by this practical dilemma, this paper develops a new method to overcome the above-mentioned two challenges simultaneously. This new method, referred as two-stage AEOQ (adaptive economic order quantity) policy

Given a grid of active and inactive pixels, the weighted rectangles partitioning (WRP) problem is to find a maximum-weight partition of the active pixels into rectangles. WRP is formulated as an integer programming problem and instances with an integral relaxation polyhedron are characterized by a balanced problem matrix. A complete characterization of these balanced instances is proved. In addition

This paper considers a movement minimization problem for mobile sensors. Given a set of n point targets, the k-Sink Minimum Movement Target Coverage Problem is to schedule mobile sensors, initially located at k base stations, to cover all targets minimizing the total moving distance of the sensors. We present a polynomial-time approximation scheme for finding a \((1+\epsilon )\) approximate solution

Community detection, as a crucial network analysis technique, holds significant application value in uncovering the underlying organizational structure in complex networks. In this paper, we propose a degree and betweenness-based label propagation method for community detection (DBLPA). First, we calculate the importance of each node by combining node degree and betweenness centrality. A node i is

For a connected graph G, an instance I is a set of pairs of vertices and a corresponding routing R is a set of paths specified for all vertex-pairs in I. Let \(\mathfrak {R}_I\) be the collection of all routings with respect to I. The undirected optical index of G with respect to I refers to the minimum integer k to guarantee the existence of a mapping \(\phi :R\rightarrow \{1,2,\ldots ,k\}\), such

For a fixed graph F, a graph G is F-saturated if G does not contain F as a subgraph, but adding any edge in \(E(\overline{G})\) will result in a copy of F. The minimum size of an F-saturated graph of order n is called the saturation number of F, denoted by sat(n, F). In this paper, we are interested in saturation problem of graph \(K_1\vee {P_t}\) for \(t\ge 2\). As some known results, \(sat(n,K_1\vee

We consider a truthful facility location game in which there is a set of agents with private locations on the line of real numbers, and the goal is to place a number of facilities at different locations chosen from the set of those reported by the agents. Given a feasible solution, each agent suffers an individual cost that is either its total distance to all facilities (sum-variant) or its distance

Despite the assortment optimization problem has been widely studied in the past decades, the interplay between advertising and its implications for this issue remains under-explored. This study seeks to bridge this research gap by tackling the combined challenge of advertising and assortment optimization. We assume that advertising can increase the awareness of specific products, and the magnitude

The paper deals with the analysis of the communicative behavior of various types of actors, speech perception and optimization of influence based on social media data and is an extended version of the report presented at CSoNet 2020 and published based on the deliverables of the conference. The paper proposes an improved methodology that is tested on the new material of conflicts regarding urban planning

Recent years have witnessed a growing trend in the utilization of Electric Vehicles (EVs), however with the increased usage of EVs, appropriate strategies for supporting the charging demands has not garnered much attention. The absence of adaptable plans in charging may result in minimized participation; further, the charging demands have to be addressed with utmost care for ensuring reliability and

Given a configuration of pebbles on the vertices of a graph G, a pebbling move removes two pebbles from a vertex and puts one pebble on an adjacent vertex. The pebbling number of a graph G is the smallest number of pebbles required such that, given an arbitrary initial configuration of pebbles, one pebble can be moved to any vertex of G through some sequence of pebbling moves. Through constructing

We propose an analytical definition of discrete circles in the hexagonal grid. Our approach is based on a non-constant thickness function. We determine the thickness using the (edge and vertex) flake model. Both types of circles are connected. We prove that edge flake circles are without simple points for integer radii. Incremental generation algorithms are deduced from the analytical characterization

In this work, we consider a combinatorial optimization problem with direct applications in blockchain mining, namely finding the most lucrative blocks for Bitcoin miners, and propose optimal algorithmic solutions. Our experiments show that our algorithms increase the miners’ revenues by more than a million dollars per month. Modern blockchains reward their miners in two ways: (i) a base reward for

Facial expression-based Emotion Recognition (FER) is crucial in human–computer interaction and affective computing, particularly when addressing diverse age groups. This paper introduces the Multi-Scale Vision Transformer with Contrastive Learning (MViT-CnG), an age-adaptive FER approach designed to enhance the accuracy and interpretability of emotion recognition models across different classes. The

This paper studies the online multiple time series search problem with interrelated prices (MTSS-ip). This perspective narrows the distance between the problem and the reality of market prices with limited variation. In MTSS-ip, the products arrive periodically, and the decision maker has a limited storage size without knowing future prices. The prices of two adjacent periods are interrelated. This

This paper introduces the concepts of spectral influence and spectral cyclicality, both derived from the largest eigenvalue of a graph’s adjacency matrix. These two novel centrality measures capture both diffusion and interdependence from a local and global perspective respectively. We propose a new clustering algorithm that identifies communities with high cyclicality and interdependence, allowing

A subset \( S\subseteq V(G) \), where V(G) is the vertex set of a graph G, is a disjunctive total dominating set of G if each vertex has a neighbour in S or has at least two vertices in S at distance two from it. The minimum cardinality of such a set is the disjunctive total domination number. There are some graph modifications on the edge or vertex of a graph, one of which is subdividing an edge.

Graph edit distance is usually used for graph similarity checking due to its low information loss and flexibility advantages. However, graph edit distance can’t be used efficiently because it is an NP-Hard problem. Many graph edit distance heuristic algorithms have been proposed to solve this problem. However, some heuristic algorithms for generating \(walk\) generate unnecessary sequences because

The selfish bin packing with partial punishment is studied in this paper. In this problem, the utility of an item is defined as the load of the bin it is in. Each item plays the role of a selfish agent and wants to maximize its own utility. If an item with size \(s_i\) moves to another bin, it has to pay the partial punishment of \(\alpha s_{i}\), where \(0<\alpha <1\). We prove that the price of anarchy

Customer segmentation, a critical strategy in marketing, involves grouping consumers based on shared characteristics like age, income, and geographical location, enabling firms to effectively establish different strategies depending on the target group of customers. Clustering is a widely utilized data analysis technique that facilitates the identification of diverse groups, each distinguished by their

In this paper we study the online over-time scheduling on an unbounded parallel-batch machine to minimize the weighted makespan. First, we show that the general problem has a low bound 2 and then design a 4-competitive online algorithm. Furthermore, we consider a special case in which the jobs have agreeable processing times and weights. When all jobs have the same weights (the task is to minimize

In this paper, we theoretically study the Combinatorial Multi-Armed Bandit problem with stochastic monotone k-submodular reward function under full-bandit feedback. In this setting, the decision-maker is allowed to select a super arm composed of multiple base arms in each round and then receives its k-submodular reward. The k-submodularity enriches the application scenarios of the problem we consider

In this paper, we present approximation algorithms for the Airport and Railway problem (AR) on several classes of graphs. The \(\text{ AR }\) problem, introduced as reported by Adamaszek et al. (in: Ollinger, Vollmer (eds) 33rd symposium on theoretical aspects of computer science (STACS 2016). Leibniz international proceedings in informatics (LIPIcs), Dagstuhl, 2016), is a combination of the Capacitated

With the rapid development of network architectures and application technologies, there is an increasing number of latency-sensitive tasks generated by user devices, necessitating real-time processing on edge servers. During peak periods, user devices compete for limited edge resources to execute their tasks, while different edge servers also compete for transaction opportunities. This article focus

In this work, we consider the Submodular Maximization under Knapsack (\(\textsf{SMK}\)) constraint problem over the ground set of size n. The problem recently attracted a lot of attention due to its applications in various domains of combinatorial optimization, artificial intelligence, and machine learning. We improve the approximation factor of the fastest deterministic algorithm from \(6+\epsilon

This paper studies a due-window assignment scheduling problem with deterioration effects on a single-machine. Under different due-window assignment, i.e., the due-window of a job without any restriction, our goal is to make a decision on the optimal due-window and sequence of all jobs to minimize the weighted sum of earliness and tardiness, number of early and delayed, due-window starting time and

The neighbor-connectivity of a graph G, denoted by \(\kappa _{NB}(G)\), is the least number of vertices such that removing their closed neighborhoods from G results in a graph that is empty, complete, or disconnected. In the paper, we show that for any graph G of order n, \(\kappa _{NB}(G)\le \lceil \sqrt{2n}\ \rceil -2\). We pose a conjecture that \(\kappa _{NB}(G)\le \lceil \sqrt{n}\ \rceil -1\)

In the field of optimization algorithms, nature-inspired techniques have garnered attention for their adaptability and problem-solving prowess. This research introduces the Arctic Fox Algorithm (AFA), an innovative optimization technique inspired by the adaptive survival strategies of the Arctic fox, designed to excel in dynamic and complex optimization landscapes. Incorporating gradient flow dynamics

In order to maximize full-view coverage of moving targets in Camera Sensor Networks (CSNs), a novel method known as “group set cover” is presented in this research. Choosing the best camera angles and placements to accomplish full-view coverage of the moving targets is one of the main focuses of the research in CSNs. Discretize the target into multiple views of [0, 2\(\pi \)], use a set of views of

We study scheduling problems with release times and rejection costs with the objective function of minimizing the maximum lateness. Our main result is a PTAS for the single machine problem with an upper bound on the rejection costs. This result is extended to parallel, identical machines. The corresponding problem of minimizing the rejection costs with an upper bound on the lateness is also examined