Graham Kendall

• BSc, PhD, FORS, FBCS
• Vice-Provost (Research & Knowledge Transfer) at University of Nottingham Malaysia Campus

We appreciate the opportunity to respond to the points raised by Oviedo-García regarding our article, “The Chinese Early Warning Journal List: Strengths, weaknesses and solutions in the light of China's global scientific rise.” We wish to provide the following clarifications in response to her Letter to the Editor.

The Cross-domain Heuristic Search Challenge (CHeSC) is a competition focused on creating efficient search algorithms adaptable to diverse problem domains. Selection hyper-heuristics are a class of algorithms that dynamically choose heuristics during the search process. Numerous selection hyper-heuristics have different implementation strategies. Ho...

The Anaesthetist Rostering Problem (ARP) presents significant challenges in healthcare management due to complex constraints and regulations. Existing models for the ARP often fail to address the complexities of real-world hospital environments, particularly in integrating monthly and weekly schedules across multiple locations. This study addresses...

There is a substantial body of scientific literature on the use of third-party services (TPS) by academics to assist as “publication consultants” in scholarly publishing. TPS provide a wide range of scholarly services to research teams that lack the equipment, skills, motivation, or time to produce a paper without external assistance. While service...

According to Scopus, China is the nation that produces the highest volume of scientific research but is also the nation with the highest number of retractions, suggesting there are issues connected to research and publishing ethics within the Chinese publishing infrastructure. One source of negative reputation may be the selection of journals with...

This survey paper presents an overview of recent application of mat-heuristics on combinatorial optimisation problems (COPs) from 2018 to 2024. In this review, we categorise the mat-heuristics into six categories based on three integration types (loose, tight and multi) and two approaches (direct and decomposition). Descriptive statistics reveal th...

h-indexes, Journal Impact Factors and CiteScores are often presented as a single numeric value, without providing any context. Under such circumstances, the reader is unable to fully appreciate, or comprehend, the information being presented. By not being transparent, it also presents the opportunity for unscrupulous operators, such as predatory jo...

Exam timetabling is a prominent topic in academic administration management as it ensures the effective utilization of resources and satisfies the requirements and preferences of stakeholders, which leads to a productive academic environment, contributing to the institution’s overall success. Given the myriad of solution methodologies explored acro...

The Physician Scheduling Problem (PSP) has emerged as a critical challenge in healthcare management, directly relevant to Sustainable Development Goal 3 (SDG 3) - Good Health and Well-being. Driven by physician shortages, rising operational costs, and the need for efficient workforce planning, PSP affects the quality of patient care, staff satisfac...

The debate surrounding “predatory publishing” continues to be unable to find entirely effective solutions to dealing with this problem, despite fervent efforts by many academics and policy makers around the world. Given this situation, we were interested in appreciating whether ChatGPT would be able to offer insight and solutions, to complement cur...

Key points Academia is already witnessing the abuse of authorship in papers with text generated by large language models (LLMs) such as ChatGPT. LLM‐generated text is testing the limits of publishing ethics as we traditionally know it. We alert the community to imminent risks of LLM technologies, like ChatGPT, for amplifying the predatory publishin...

The SCImago Journal Rank (SJR) ranks journals into four quartiles (Q1–Q4). SJR serves as a safelist for journal selection, when trying to avoid predatory journals, as journals that have been indexed by SJR are seen as having stringent publishing standards. An AI-based tool, the Academic Journal Predatory Checking System (AJPC), claims to be able to...

Academics (should) strive to submit to journals which are academically sound and scholarly. To achieve this, they could either submit to journals that appear exclusively on safelists (occasionally referred to as whitelists, although this term tends to be avoided), or avoid submitting to journals on watchlists (occasionally referred to as blacklists...

This survey paper provides an overview of current developments for the Portfolio Optimisation Problem (POP) based on articles published from 2018 to 2022. It reviews the latest solution methodologies utilised in addressing POPs in terms of mechanisms and performance. The methodologies are categorised as Metaheuristic, Mathematical Optimisation, Hyb...

In this paper, an improved discrete Grey Wolf Optimizer (ID-GWO) is proposed to address a benchmark nurse rostering problem (NRP). We propose a discrete grey wolf optimizer (D-GWO) by utilizing the neighborhood structures commonly found in the literature as mutation operators. The D-GWO is further improved by modifying the crossover operator to enh...

Peer review underpins the integrity of the scientific archive and has done so for over 350 years. Over the past ten years or so, this integrity has come under pressure due to the introduction of predatory publishers and journals. Papers in predatory journals have, typically, not gone through robust peer review, if any at all. If these papers enter...

Between 2009 and 2012, Jeffrey Beall analyzed 18 publishers, which were publishing 1328 journals. He classified all but one of the publishers as predatory. In this paper we look again at these publishers to see what has changed since that initial analysis. We focus on the same 18 publishers so that we have a direct comparison with Beall’s original...

Publons currently has 1.7 million researchers on its database, who have registered 10.8 million reviews. The top ten Publons reviewers review at least one paper every 2 days. Three of the top ten reviewers have reviewed at least one paper every day since 2006 (resp. 2010 and 2013). That is, for the past 16 (resp. 12 and 9) years these reviewers hav...

The uniqueness of equilibrium in bargaining games with three or more players is a problem preventing bargaining theory from general real world applications. We study the uniqueness of bargaining equilibrium in a bargaining game of two sellers and two buyers, which has instances in real-world markets. Each seller (or buyer) wants to reach an agreeme...

Information on lower bounds plays an important role in the development of exact and heuristic methods for stochastic service network design (SSND). In this paper, we consider the Lagrange dual problem of SSND for computing lower bounds. The Lagrange dual problem is obtained by introducing scenario bundling into scenario-wise decomposition of the SS...

This paper presents an overview of recent advances for the Nurse Rostering Problem (NRP) based on methodological papers published between 2012 to 2021. It provides a comprehensive review of the latest solution methodologies, particularly computational intelligence (CI) approaches, utilized in benchmark and real-world nurse rostering. The methodolog...

In this paper, we are addressing the NP-hard nurse rostering problem utilizing a 2-stage approach. In stage one, Monte Carlo Tree Search (MCTS) and Hill Climbing (HC) are hybridized in finding a feasible solution (satisfying all the hard constraints). We propose a new constant $C$ value (which balances search diversification and intensification o...

The Master Surgery Scheduling Problem (MSSP) allocates operating theatre time to surgery groups such as medical specialities or surgeons, which is essential for daily operational planners. Many researchers have highlighted issues in the optimization of surgical scheduling problems. However, most recent reviews limited the issues at the operational...

The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed. To tackle the complexities, uncertainties and dynamics involved in real-world VRP applications, Machine Learning (ML) methods have been used in combination with analytical approach...

In this paper, a PSO-based algorithm that hybridized Particle Swarm Optimization (PSO) and Hill Climbing (HC) is applied to high school timetabling problem. This hybrid has two features, a novel solution transformation and particle elimination. The proposed methodologies are tested on the XHSTT-2014 dataset (which is relatively new for the school t...

One way of exposing predatory journals is to submit a spoof article to see if it gets accepted. We investigate one journal, looking at how it has performed since a spoof paper it accepted came to light. We find that it has published almost 20% more papers following the acceptance of the spoof paper. The journal has a new web site, which appears to...

This paper is an orthogonal study to that of Kendall and Lenten (2017)—on the perverse unintended consequences of badly designed sports rules. This paper, unlike the previous one, focuses on the positive narrative by aggregating a collection of academic work proposing rule change ideas, some of which have been implemented already. We also discuss f...

This article addresses the dynamic vehicle routing problem (DVRP). DVRP is a challenging variation of the classic vehicle routing problem in which some customers are not known in advance. The objective is to incorporate new customers into the schedule as they become known while still attempting to minimize the cost of serving all customers without...

The timetabling problem is common to academic institutions such as schools, colleges or universities. It is a very hard combinatorial optimisation problem which attracts the interest of many researchers. The university course timetabling problem (UCTTP) is difficult to address due to the size of the problem and several challenging hard and soft con...

The Vehicle Routing Problem (VRP) was formally presented to the scientific literature in 1959 by Dantzig and Ramser (DOI:10.1287/mnsc.6.1.80). Sixty years on, the problem is still heavily researched, with hundreds of papers having been published addressing this problem and the many variants that now exist. Many datasets have been proposed to enable...

The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed. To tackle the complexities, uncertainties and dynamics involved in real-world VRP applications, Machine Learning (ML) methods have been used in combination with analytical approach...

Between 2009 and 2012, Jeffrey Beall published four articles which analysed 18 publishers (17 of which he identified as predatory). He also introduced the term predatory in the context of scientific publishing. In 2012, he started Beall's List, which maintained a list of predatory publishers and journals. This became a valuable resource for those w...

We present a method for bundling scenarios in a progressive hedging heuristic (PHH) applied to stochastic service network design, where the uncertain demand is represented by a finite number of scenarios. Given the number of scenario bundles, we first calculate a vector of probabilities for every scenario, which measures the association strength of...

Educational timetabling is an ongoing challenging administrative task that is required in most academic institutions. This is mainly due to a large number of constraints and requirements that have to be satisfied. Educational timetabling problems have been classified as NP-hard problems and can be divided into three types: exam timetabling, course...

We address the post enrolment course timetabling (PE-CTT) problem in this paper. PE-CTT is known as an NP-hard problem that focuses on finding an efficient allocation of courses onto a finite number of time slots and rooms. It is one of the most challenging resources allocation problems faced by universities around the world. This work proposes a t...

The paper investigates a partial exam assignment approach for solving the examination timetabling problem. Current approaches involve scheduling all of the exams into time slots and rooms (i.e., produce an initial solution) and then continuing by improving the initial solution in a predetermined number of iterations. We propose a modification of th...

The bird mating optimizer is a new metaheuristic algorithm that was originally proposed to solve continuous optimization problems with a very promising performance. However, the algorithm have not yet been applied for solving combinatorial optimization problems. Thus, the formulation may not be able to generate a discrete feasible solution. Many co...

Hosting film festivals has become a prevailing practice to promote culture or festival tourism. Empirical studies on the relationship between cultural attendance and tourism demands, however, were mainly comprised of investigations of data of one or very few countries. In this study, by conducting dynamic panel data analysis, with secondary data ac...

This paper defines a new combinatorial optimization problem, namely General Combinatorial Optimization Problem (GCOP), whose decision variables are a set of parametric algorithmic components, i.e. algorithm design decisions. The solutions of GCOP, i.e. compositions of algorithmic components, thus represent different generic search algorithms. Th...

Background and objectives: In cancer therapy optimization, an optimal amount of drug is determined to not only reduce the tumor size but also to maintain the level of chemo toxicity in the patient's body. The increase in the number of objectives and constraints further burdens the optimization problem. The objective of the present work is to solve...

We are addressing the course timetabling problem in this work. In a university, students can select their favorite courses each semester. Thus, the general requirement is to allow them to attend lectures without clashing with other lectures. A feasible solution is a solution where this and other conditions are satisfied. Constructing reasonable sol...

The performance of data clustering algorithms is mainly dependent on their ability to balance between the exploration and exploitation of the search process. Although some data clustering algorithms have achieved reasonable quality solutions for some datasets, their performance across real-life datasets could be improved. This paper proposes an ada...

Multi-label text categorization refers to the problem of assigning each document to a subset of categories by means of multi-label learning algorithms. Unlike English and most other languages, the unavailability of Arabic benchmark datasets prevents evaluating multi-label learning algorithms for Arabic text categorization. As a result, only a few r...

In the book Thirteen Against the Bank, Norman Leigh claims to have achieved the impossible and devised a system to consistently return a profit from playing roulette. It sounds too good to be true, and maybe it is. Graham Kendall uses computer simulation to sort fact from fiction In the book Thirteen Against the Bank, Norman Leigh claims to have ac...

RTAnews dataset is a collections of multi-label Arabic texts, collected form Russia Today in Arabic news portal. It consists of 23,837 texts (news articles) distributed over 40 categories, and divided into 15,001 texts for the training and 8,836 texts for the test. The original dataset (without preprocessing), a preprocessed version of the dataset...

In this paper, we utilise a two-stage approach for addressing the post enrolment course timetabling (PE-CTT) problem. We attempt to find a feasible solution in the first stage. The solution is further improved in terms of soft constraint violations in the second stage. We present an enhanced variant of the Simulated Annealing with Reheating (SAR) a...

Due to increased search complexity in multi-objective optimization, premature convergence becomes a problem. Complex engineering problems poses high number of variables with many constraints. Hence, more difficult benchmark problems must be utilized to validate new algorithms performance. A well-known optimizer, Multi-Objective Particle Swarm Optim...

Presents a summary of recent books of interest to computer scientists and engineers.

Presents reviews of recent articles from select IEEE publications.

Service network design is used in less-than-truckload (LTL) transportation to address the selection, routing and scheduling of services, with the aim of making good cost-savings while rendering excellent service. Compared to the intensively studied vehicle routing problems (VRP), service network design provides is a better way to model the freight...

The orienteering problem (OP) is a routing problem that has numerous applications in various domains such as logistics and tourism. The objective is to determine a subset of vertices to visit for a vehicle so that the total collected score is maximized and a given time budget is not exceeded. The extensive application of the OP has led to many diff...

Evolutionary Computation (EC) has been an active research area for over 60 years, yet its commercial/home uptake has not been as prolific as we might have expected. By way of comparison, technologies such as 3D printing, which was introduced about 35 years ago, has seen much wider uptake, to the extent that it is now available to home users and is...

Global research and development (R&D) spending has increased in recent years as the need for new technologies has grown and structural changes in the market have become evident. R&D and its transfer into the commercial sector have an important relationship. This paper analyzes the relationship between industrial R&D expenditure and how it affects t...

Formulating feed for shrimps represents a challenge to farmers and industry partners. Most previous studies selected from only a small number of ingredients due to cost pressures, even though hundreds of potential ingredients could be used in the shrimp feed mix. Even with a limited number of ingredients, the best combination of the most appropriat...

A company's Information Technology (IT) infrastructure is a key factor in its sustainability and ongoing success and profitability. This paper explores the relationship between a company's investment in IT and its performance. Performance is measured, with the help of a Balanced Scorecard (BSC), in four ways; financial, internal business processes,...

Presents a listing of books recently published in the field of computational intelligence.

Presents a synopsis of the latest books in the area of computational intelligence.

Fed-batch fermentation has gained attention in recent years due to its beneficial impact in the economy and productivity of bioprocesses. However, the complexity of these processes requires an expert system that involves swarm intelligence-based metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix...

Presents a synopsis of the latest books in the area of computational intelligence.

Purpose The purpose of this paper is to support the use of unique identifiers for the authors of scientific publications. This, the authors believe, aligns with the views of many others, as it would solve the problem of author disambiguation. If every researcher had a unique identifier, there would be significant opportunities to provide even more...

Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t-way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Harmony Search (HS). Although useful...

Software testing relates to the process of accessing the functionality of a program against some defined specifications. To ensure conformance, test engineers often generate a set of test cases to validate against the user requirements. Owing to the growing complexity of software and its increasing diffusion into various application domains, it is...

Presents a summary of articles from various publications that focus on the computational intelligent industry.

In this work, we are addressing the post enrollment course timetabling (PE-CTT) problem. We combine different local search algorithms into an iterative two stage procedure. In the first stage, Tabu Search with Sampling and Perturbation (TSSP) is used to generate feasible solutions. In the second stage, we propose an improved variant of Simulated An...

Type-reduction of type-2 fuzzy sets is considered to be a defuzzification bottleneck because of the computational complexity involved in the process of type-reduction. In this research, we prove that the closed-form Nie-Tan operator, which outputs the average of the upper and lower bounds of the footprint of uncertainty, is actually an accurate met...

In this paper, a dynamic truck dispatching problem of a marine container terminal is described and discussed. In this problem, a few containers, encoded as work instructions, need to be transferred between yard blocks and vessels by a fleet of trucks. Both the yard blocks and the quay are equipped with cranes to support loading/unloading operations...

Presents a synopsis of the latest books in the area of computational intelligence.

When a scientific paper, dissertation or thesis is published the author(s) have a duty to report who has contributed to the work. This recognition can take several forms such as authorship, relevant acknowledgments and by citing previous work. There is a growing industry where publication consultants will work with authors, research groups or even...

In freight transportation, less-than-truckload carriers often need to assign each vehicle a cyclic route so that drivers can come back home after a certain period of time. However, the Node-Arc model for service network design addresses decisions on each arc and does not determine routes directly, although the vehicle balancing constraint ensures t...

Presents information on recent articles published in the field of computational intelligence.

This paper proposes a novel hybrid t-way test generation strategy (where t indicates interaction strength), called High Level Hyper-Heuristic (HHH). HHH adopts Tabu Search as its high level meta-heuristic and leverages on the strength of four low level meta-heuristics, comprising of Teaching Learning based Optimization, Global Neighborhood Algorith...

Mike Wright (Wright, M. OR analysis of sporting rules – A survey. European Journal of Operational Research, 232(1):1–8, 2014) recently presented a survey of sporting rules from an Operational Research (OR) perspective. He surveyed 21 sports, which consider the rules of sports and tournaments and whether changes have led to unintended consequences....

In this paper, a genetic algorithm with minimum description length (GAWMDL) is proposed for grammatical inference. The primary challenge of identifying a language of infinite cardinality from a finite set of examples should know when to generalize and specialize the training data. The minimum description length principle that has been incorporated...

Recently, interest in solving real-world problems that change over the time, so called dynamic optimisation problems (DOPs), has grown due to their practical applications. A DOP requires an optimisation algorithm that can dynamically adapt to changes and several methodologies have been integrated with population-based algorithms to address these pr...

Hyper-heuristics are (meta-)heuristics that operate at a higher level to choose or generate a set of low-level (meta-)heuristics in an attempt of solve difficult optimization problems. Iterated local search (ILS) is a well-known approach for discrete optimization, combining perturbation and hill-climbing within an iterative framework. In this study...

Landing aircraft safely is an important operation that air traffic controllers have to deal with on a daily basis. For each arriving aircraft a runway and a landing time must be allocated. If these allocations can be done in an efficient way, it could give the airport a competitive advantage. The Aircraft Landing Problem (ALP) aims to minimize the...

Good Laboratory Practice has been a part of non-clinical research for over 40 years yet. Optimization Research, despite having many papers discussing standards being published over the same period of time, has yet to embrace standards that underpin its research. In this paper we argue the need to adopt standards in optimization research. Building o...

Stability analysis is an important research direction in evolutionary game theory. Evolutionarily stable states have a close relationship with Nash equilibria of repeated games, which are characterized by the folk theorem. When applying the folk theorem, one needs to compute the minimax profile of the game in order to find Nash equilibria. Computin...

Hyper-heuristics aim to automate the heuristic selection process in order to operate well across different problem instances, or even across different problem domains. A traditional hyper-heuristic framework has two levels, a high level strategy and a set of low level heuristics. The role of the high level strategy is to decide which low level heur...

This paper proposes a new method to evaluate Decision Making Units (DMUs) under uncertainty using fuzzy Data Envelopment Analysis (DEA). In the proposed multi-objective nonlinear programming methodology both the objective functions and the constraints are considered fuzzy. The coefficients of the decision variables in the objective functions and in...

In evolutionary game theory, evolutionarily stable states are characterised by the folk theorem because exact solutions to the replicator equation are difficult to obtain. It is generally assumed that the folk theorem, which is the fundamental theory for non-cooperative games, defines all Nash equilibria in infinitely repeated games. Here, we prove...

This paper presents a hybrid hyper-heuristic approach based on estimation distribution algorithms. The main motivation is to raise the level of generality for search methodologies. The objective of the hyper-heuristic is to produce solutions of acceptable quality for a number of optimisation problems. In this work, we demonstrate the generality thr...

Imperfection of information is a part of our daily life; however, it is usually ignored in learning based on evolutionary approaches. In this paper we develop an Imperfect Evolutionary System that provides an uncertain and chaotic imperfect environment that presents new challenges to its habitants. We then propose an intelligent methodology which i...

This paper expands on the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm in search of greater performance benefits. Evaluation of various strategies on a diverse set of floating-point benchmark problems shows that heurist...

This paper investigates the potential of Artificial Immune Systems (AIS) in solving the channel allocation problem in wireless communication. The main objective is to find the minimum number of channels to satisfy the demands of a network without violating any given constraints. The proposed methodology is applied to new datasets which were generat...

Purpose – The purpose of this paper is to identify the most significant barriers to successful implementation of information technology (IT) in higher educational institutions (HEIs) of India. Although, educational institutions are investing in IT, they have been not been able to leverage it the same way as other business organizations. The present...

Hyper-heuristics are emerging methodologies that perform a search over the space of heuristics to solve difficult computational optimization problems. There are two main types of hyper-heuristics: selective and generative hyper-heuristics. An online selective hyper-heuristic framework manages a set of low level heuristics and aims to choose the bes...

Presents the introductory editorial from this issue of the publication.

Lists recently published books in the area of computational intelligence.

Hyper-heuristics have been successfully applied in solving a variety of computational search problems. In this study, we investigate a hyper-heuristic methodology to generate adaptive strategies for games. Based on a set of low-level heuristics (or strategies), a hyper-heuristic game player can generate strategies which adapt to both the behaviour...

The berth allocation problem (BAP) is an important and challenging problem in the maritime transportation industry. BAP can be defined as the problem of assigning a berth position and service time to a given set of vessels while ensuring that all BAP constraints are respected. The goal is to minimize the total waiting time of all vessels. In this p...

In evolutionary game theory, evolutionarily stable states are characterised by the folk theorem because exact solutions to the replicator equation are difficult to obtain. It is generally assumed that the folk theorem, which is the fundamental theory for non-cooperative games, defines all Nash equilibria in infinitely repeated games. Here, we prove...

Portfolio optimization involves the optimal assignment of limited capital to different available financial assets to achieve a reasonable trade-off between profit and risk objectives. In this paper, we studied the extended Markowitz's mean-variance portfolio optimization model. We considered the cardinality, quantity, pre-assignment and round lot c...