The resolution of workshop problems, such as the Flow Shop or the Job Shop, has great importance in industrial areas. Criteria to optimize are generally the minimization of the makespan time or the tardiness time. However, few resolution approaches take into account those different criteria simultaneously. This paper presents a comparative and progressive study of different multicriteria optimization techniques. Several strategies of selection, diversity maintaining, and hybridization will be exposed. Their performances will be compared and tested. A parallel GA model is proposed, which allows increasing the population size and the limit generations number, and leads to better results. In parallel to the work on the optimization technique, we propose here a new bi-criteria flow shop benchmark, responding to the need for common problem instances in the field of multicriteria optimization.

In this paper we determine a class of critical sets in the abelian \(2\)-group that may be obtained from a greedy algorithm. These new critical sets are all \(2\)-critical (each entry intersects an intercalate, a trade of size \(4\)) and complete in a top-down manner.

In a \((k, n)\)-threshold scheme, a secret key \(K\) is split into \(n\) shares in such a way that \(K\) can be recovered from \(k\) or more shares, but no information about \(K\) can be obtained from any \(k-1\) or fewer shares. We are interested in the situation where there are some number of incorrect (i.e., faulty) shares. When there are faulty shares, we might need to examine more than \(k\) shares in order to reconstruct the secret correctly. Given an upper bound, namely \(t\), on the number of faulty shares, we focus on finding efficient algorithms for reconstructing the secret in a \((k, n)\)-threshold scheme. We call this the threshold scheme with cheaters problem.

We first review known combinatorial algorithms that use covering designs, as presented in Rees et al. [11] and Tso et al. [13]. Then we extend the ideas of their algorithms to a more general one. We also link the threshold scheme with cheaters problem to decoding generalized Reed-Solomon codes. Then we adapt two decoding algorithms, namely, the Peterson-Gorenstein-Zierler Algorithm and Gao’s Algorithm, to solve our problem. Finally, we contribute a general algorithm that combines both the combinatorial and decoding approaches, followed by an experimental analysis of all the algorithms we describe.

Let \( G \) be a simple graph, and let \( p \) be a positive integer. A subset \( D \subseteq V(G) \) is a \( p \)-\({dominating}\) set of the graph \( G \), if every vertex \( v \in V(G) – D \) is adjacent to at least \( p \) vertices of \( D \). The \( p \)-domination number \( \gamma_p(G) \) is the minimum cardinality among the \( p \)-dominating sets of \( G \). Note that the \( 1 \)-domination number \( \gamma_1(G) \) is the usual domination number \( \gamma(G) \). The covering number of a graph \( G \) is denoted by \( \beta(G) \). If \( T \) is a tree of order \( n(T) \), then Fink and Jacobson [1] proved in 1985 that

\[\gamma_p(T) \geq \frac{(p-1)n(T) + 1}{p}\]

The special case \( p = 2 \) of this inequality easily leads to

\[\gamma_2(T) \geq \beta(T) + 1 \geq \gamma(T) + 1\]

for every non-trivial tree \( T \). Inspired by the article of Fink and Jacobson [1], we characterize in this paper the family of trees \( T \) with \( \gamma_p(T) = \left\lceil \frac{(p-1)n(T) + 1}{p} \right\rceil \) as well as all non-trivial trees \( T \) with \( \gamma_2(T) = \gamma(T) + 1 \) and \( \gamma_2(T) = \beta(T) + 1 \).

Alliances in undirected graphs were introduced by Hedetniemi, Hedetniemi, and Kristiansen, and generalized to \( k \)-alliances by Shafique and Dutton. We translate these definitions of alliances to directed graphs. We establish basic properties of alliances and examine bounds on the size of minimal alliances in directed graphs. In general, the bounds established for alliances in undirected graphs do not hold when alliances are considered over the larger class of directed graphs and we construct examples which break these bounds.

For given integers \( k \) and \( \ell \), \( 3 \leq k \leq \ell \), a graphic sequence \( \pi = (d_1, d_2, \dots, d_n) \) is said to be potentially \({}_{k}C_\ell\)-graphic if there exists a realization of \( \pi \) containing \( C_r \), for each \( r \), where \( k \leq r \leq \ell \) and \( C_r \) is the cycle of length \( r \). Luo (Ars Combinatoria 64(2002)301-318) characterized the potentially \( C_\ell \)-graphic sequences without zero terms for \( r = 3, 4, 5 \). In this paper, we characterize the potentially \({}_{k}C_\ell\)-graphic sequences without zero terms for \( k = 3, 4 \leq \ell \leq 5 \) and \( k = 4, \ell = 5 \).

We show that deciding if a set of vertices is an eternal \(1\)-secure set is complete for \(\text{co-}NP^{\text{NP}}\), solving a problem stated by Goddard, Hedetniemi, and Hedetniemi \([JCMCC, \text{vol. 52}, \text{pp. 160-180}]\).

A Sarvate-Beam type of triple system is defined in the case \( v \equiv 2 \pmod{3} \) and an enumeration is given of such systems for \( v = 5 \).

Informally, a set of guards positioned on the vertices of a graph \( G \) is called eternally secure if the guards are able to respond to vertex attacks by moving a single guard along a single edge after each attack regardless of how many attacks are made. The smallest number of guards required to achieve eternal security is the eternal security number of \( G \), denoted \( es(G) \), and it is known to be no more than \( \theta_v(G) \), the vertex clique cover number of \( G \). We investigate conditions under which \( es(G) = \theta_v(G) \).

We apply Computational Algebra methods to the construction of Hadamard matrices from two circulant submatrices, given by C. H. Yang. We associate Hadamard ideals to this construction, to systematize the application of Computational Algebra methods. Our approach yields an exhaustive search for Hadamard matrices from two circulant submatrices for this construction, for the first eight admissible values \(2, 4, 8, 10, 16, 18, 20, 26\) and partial searches for the next three admissible values \(32, 34, 40\). From the solutions we found, for the admissible values \(26\) and \(34\), we located new inequivalent Hadamard matrices of orders \(52\) and \(68\) with two circulant submatrices, thus improving the lower bounds for the numbers of inequivalent Hadamard matrices of orders \(52\) and \(68\). We also propose a heuristic decoupling of one of the equations arising from this construction, which can be used together with the PSD test to search for solutions more efficiently.