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While changing a very long tabular into a supertabular, I had a problem having the supertabular* being equivalent to tabular*, but just continuing on the next pages. To give an example, I don't want the table to continue in the following column like in this post about balancing it, but more something equivalent to this post with the table on both columns, continuing on next pages. The last one being with xtab, I tried it and had a similar result.

It may be--after investigating--linked to \dimexpr in "horizontal mode", that is somehow trigerred by supertabular*, but I don't uderstand the error.

Here is my (M)WE:

\documentclass[twocolumn]{article}
\usepackage{supertabular, booktabs}
\newcommand{\tabitem}{~~\llap{\textbullet}~~}

\usepackage{array} %% Array m option in particular (center and sized)
\usepackage{diagbox} %% Array diagonal box
\usepackage{multirow} %for multi row in table

\begin{document}

Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;


\begin{center}
\tablefirsthead{%
\toprule
AI/ML Models & Prediction & Optimisation/ Automation & Analysis & Modelling/
Simulation \\ \midrule \\
}
\tablehead{%
%\hline\multicolumn{4}{|l|}{\small\sl continued from previous page}\\
\toprule
AI/ML Models & Prediction & Optimisation/ Automation & Analysis & Modelling/
Simulation \\ \midrule \\
}
\tabletail{%
\bottomrule
\multicolumn{5}{c}{\small continued on next page} \\
\bottomrule \\
}
\tablelasttail{%
\bottomrule \\
}

\tablecaption{Publication Distribution with the Design Space}
\label{tab: designSpace} 

\begin{supertabular*}{@{}p{\dimexpr 0.20\textwidth-\tabcolsep \relax}p{\dimexpr 0.22\textwidth-2\tabcolsep \relax}p{\dimexpr 0.20\textwidth-2\tabcolsep \relax}p{\dimexpr 0.18\textwidth-2\tabcolsep \relax}p{\dimexpr 0.20\textwidth-\tabcolsep\relax }@{}}
%\begin{supertabular}{lllll}


%\endhead
Multi-Agent System (MAS) 
&
& 
&  
& 
\\  


Evolutionary Algorithm (EA) 
&  
& 
& 
& \\

Simulated Annealing (SA) 
& 
& 
& 
& \\  

Tabu search 
& 
&  
& 
& \\  

Particle Swarm Optimisation 
& 
&  
& 
& \\  

Ant Colony Algorithm 
& 
&  
& 
& \\  

Bee Colony Algorithm
&
& 
&
& \\


Neural Network (NN) 
& 
& 
& 
& \\  

Deep Deterministic Policy Gradient (DDPG) 
& 
& 
& 
& \\  

Convolutional Neural Networks (CNN)
& 
&
&
& \\

Deep Q-Network (DQN) 
& 
&  
& 
& \\  

Deep Learning
& 
&
&
& \\
Autoencoder
& 
&
&
&  \\

Random Forest (RF) 
& 
&
& 
& \\  

Quantile Regression Forest 
&  
& 
& 
& \\   

Gradient Boosting Machine (GBM) 
& 
& 
& 
& \\  

Support Vector Machine (SVM) 
& 
&  
& 
& \\  

Decision Tree 
& 
& 
& 
&  \\  

Fuzzy Logic 
&  
& 
& 
& \\  

Linear Regression 
& 
&  
& 
&  \\  

Linear Functional Regression 
& 
& 
& 
& \\  

Linear Discriminant Analysis (LDA)
&  
& 
& 
& \\

Quadratic Discriminant Analysis (QDA)
&  
& 
& 
& \\

Logistic regression
& 
& 
& 
& \\  

Binary logistic regression models 
& 
& 
&  
& \\  

Gaussian Mixture Model 
& 
& 
& 
& \\  

Bayesian Network 
& 
& 
& 
&  \\  

Recursive Bayesian estimation 
& 
&  
& 
& \\  

k-nearest neighbor (k-NN)
& 
&
&
&\\

Genetic algorithm 
&
& 
&
& \\

Hierarchical clustering
&
&
&
& \\

Dynamic Bayesian Belief Network 
&  
& 
& 
&  \\  

BIRCH 
& 
& 
&  
& \\  

DBSCAN
& 
& 
&  
& \\  

OPTIC 
& 
& 
&  
& \\  

K-means 
& 
& 
&   
& \\  

Non Negative Matrix Factorisation (NMF) 
& 
&  
& 
& \\  

A* 
& 
& 
& 
& \\  

Multi-Layer Perceptron (MLP)
& 
& 
& 
& \\ 

Deep Reinforcement Learning
& 
& 
& 
& \\ 

Recurrent neural network \& LSTM
& 
&
&
& \\

Reinforcement Learning
& 
& 
& 
& \\ 

k-nearest neighbours (kNN)
& 
& 
& 
& \\ 

Principal Component Analysis (PCA)
& 
&
&
& \\

OPTICS clustering
&
&
&
& \\

Not referenced 
&  
&  
& 
& \\  


\end{supertabular*}
\end{center}

Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;Some text;
\end{document}

Many thanks.

Edit: Wanted result

1 Answer 1

0

So, I will post an anwser to my question, although not ideal to me, I used the "strip" environment from the "cuted" package, using \shrinkheight{} from the supertabular package to modify accordingly the first split of the table. Solution was made thanks to this post, especially the anwser from Bernard using xtab (and not supertabular). If anyone can make supertabular* environment work, please tell me, I would love to understand the problem.

\documentclass[twocolumn]{article}
    \usepackage{supertabular, booktabs}
\newcommand{\tabitem}{~~\llap{\textbullet}~~}
\usepackage{cuted}
\usepackage{array} %% Array m option in particular (center and sized)
\usepackage{diagbox} %% Array diagonal box
\usepackage{multirow} %for multi row in table
%\usepackage{xtab, booktabs}
\usepackage{blindtext}

\begin{document}

\blindtext[4]


%\begin{center}
 \begin{strip}
 \centering
 %\setlength{\extrarowheight}{2pt}
\tablefirsthead{%
\toprule
AI/ML Models & Prediction & Optimisation/ Automation & Analysis & Modelling/
Simulation \\ \midrule \\
}
\tablehead{%
%\hline\multicolumn{4}{|l|}{\small\sl continued from previous page}\\
\toprule
AI/ML Models & Prediction & Optimisation/ Automation & Analysis & Modelling/
Simulation \\ \midrule \\
}
\tabletail{%
\bottomrule
\multicolumn{5}{c}{\small continued on next page} \\
\bottomrule \\
}
\tablelasttail{%
\bottomrule \\
}

\tablecaption{Publication Distribution with the Design Space}
\label{tab: designSpace} 

\begin{supertabular}{@{}p{\dimexpr 0.20\textwidth-\tabcolsep \relax}p{\dimexpr 0.22\textwidth-2\tabcolsep \relax}p{\dimexpr 0.20\textwidth-2\tabcolsep \relax}p{\dimexpr 0.18\textwidth-2\tabcolsep \relax}p{\dimexpr 0.20\textwidth-\tabcolsep\relax }@{}}
%\begin{supertabular*}{p{0.20\textwidth}p{0.22\textwidth}p{0.20\textwidth}p{0.18\textwidth}p{ 0.20\textwidth}}

Multi-Agent System (MAS) 
&
& 
&  
& \\  
\shrinkheight{-60ex}

Evolutionary Algorithm (EA) 
&  
& 
& 
& \\

Simulated Annealing (SA) 
& 
& 
& 
& \\  

Tabu search 
& 
&  
& 
& \\  

Particle Swarm Optimisation 
& 
&  
& 
& \\  

Ant Colony Algorithm 
& 
&  
& 
& \\  

Bee Colony Algorithm
&
& 
&
& \\


Neural Network (NN) 
& 
& 
& 
& \\  

Deep Deterministic Policy Gradient (DDPG) 
& 
& 
& 
& \\  

Convolutional Neural Networks (CNN)
& 
&
&
& \\

Deep Q-Network (DQN) 
& 
&  
& 
& \\  

Deep Learning
& 
&
&
& \\
Autoencoder
& 
&
&
&  \\

Random Forest (RF) 
& 
&
& 
& \\  

Quantile Regression Forest 
&  
& 
& 
& \\   

Gradient Boosting Machine (GBM) 
& 
& 
& 
& \\  

Support Vector Machine (SVM) 
& 
&  
& 
& \\  

Decision Tree 
& 
& 
& 
&  \\  

Fuzzy Logic 
&  
& 
& 
& \\  

Linear Regression 
& 
&  
& 
&  \\  

Linear Functional Regression 
& 
& 
& 
& \\  

Linear Discriminant Analysis (LDA)
&  
& 
& 
& \\

Quadratic Discriminant Analysis (QDA)
&  
& 
& 
& \\

Logistic regression
& 
& 
& 
& \\  

Binary logistic regression models 
& 
& 
&  
& \\  

Gaussian Mixture Model 
& 
& 
& 
& \\  

Bayesian Network 
& 
& 
& 
&  \\  

Recursive Bayesian estimation 
& 
&  
& 
& \\  

k-nearest neighbor (k-NN)
& 
&
&
&\\

Genetic algorithm 
&
& 
&
& \\

Hierarchical clustering
&
&
&
& \\

Dynamic Bayesian Belief Network 
&  
& 
& 
&  \\  

BIRCH 
& 
& 
&  
& \\  

DBSCAN
& 
& 
&  
& \\  

OPTIC 
& 
& 
&  
& \\  

K-means 
& 
& 
&   
& \\  

Non Negative Matrix Factorisation (NMF) 
& 
&  
& 
& \\  

A* 
& 
& 
& 
& \\  

Multi-Layer Perceptron (MLP)
& 
& 
& 
& \\ 

Deep Reinforcement Learning
& 
& 
& 
& \\ 

Recurrent neural network \& LSTM
& 
&
&
& \\

Reinforcement Learning
& 
& 
& 
& \\ 

k-nearest neighbours (kNN)
& 
& 
& 
& \\ 

Principal Component Analysis (PCA)
& 
&
&
& \\

OPTICS clustering
&
&
&
& \\

Not referenced 
&  
&  
& 
& \\  


\end{supertabular}
%\end{center}
\end{strip}

\blindtext[4]

\end{document}

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