In this paper, we show that for every sufficiently large integer \(n\) and every positive integer \(c \leq \left\lfloor \frac{1}{6}({\log \log n})^\frac{1}{2} \right \rfloor\), a Boolean lattice with \(n\) atoms can be partitioned into chains of cardinality \(c\), except for at most \(c-1\) elements which also form a chain.

We construct all self-dual \([24, 12, 8]\) quaternary codes with a monomial automorphism of prime order \(r > 3\) and obtain a unique code for \(r = 23\) (which has automorphisms of orders \(5\), \(7\), and \(11\) too), two inequivalent codes for \(r = 11\), \(6\) inequivalent codes for \(r = 7\), and \(12\) inequivalent codes for \(r = 5\). The obtained codes have \(12\) different weight spectra.

Metamorphoses of small \(k\)-wheel systems for \(k = 3, 4,\) and \(6\) are obtained. In particular, we obtain simultaneous metamorphoses of: \(3\)-wheel systems into Steiner triple systems and into \(K_{1,3}\)-designs; \(4\)-wheel systems into \(4\)-cycle systems, \(K_{1,4}\)-designs, and bowtie systems; \(6\)-wheel systems into \(6\)-cycle systems, \(K_{1,6}\)-designs, and \(3\)-windmill designs or near-\(3\)-windmill designs.

We deal with the problem of labeling the vertices, edges, and faces of a plane graph in such a way that the label of a face and the labels of the vertices and edges surrounding that face add up to a weight of that face, and the weights of all the faces constitute an arithmetical progression of difference \(d\).

If \(L\) is a list assignment function and \(\kappa\) is a multiplicity function on the vertices of a graph \(G\), a certain condition on \((G, L, \kappa)\), known as Hall’s multicoloring condition, is obviously necessary for the existence of a multicoloring of the vertices of \(G\). A graph \(G\) is said to be in the class \(MHC\) if it has a multicoloring for any functions \(L\) and \(\kappa\) such that \((G, L, \kappa)\) satisfies Hall’s multicoloring condition. It is known that if \(G\) is in \(MHC\) then each block of \(G\) is a clique and each cutpoint lies in precisely two blocks. We conjecture that the converse is true as well. It is also known that if \(G\) is a graph consisting of two cliques joined at a point then \(G\) is in \(MHC\). We present a new proof of this result which uses common partial systems of distinct representatives, the relationship between matching number and vertex covering number for 3-partite hypergraphs, and Menger’s Theorem.

This paper presents a new approach in the quest for a solution to the \(3x+1\) problem. The method relies on the convergence of the trajectories of the odd positive integers by exploiting the role of the positive integers of the form \(1+4n\), where \(n\) is a non-negative integer.

A cyclic or bicyclic \(9 \times 37\) double Youden rectangle (DYR) is provided for each of the four biplanes with \(k = 9\). These DYRs were obtained by computer search.

For loopless plane multigraphs \(G\), the edge-face chromatic number and the entire chromatic number are asymptotically their fractional counterparts (LP relaxations) as these latter invariants tend to infinity. Proofs of these results are based on analogous theorems for the chromatic index and the total chromatic number, due, respectively, to Kahn [3] and to the first author [6]. Our two results fill in the missing pieces of a complete answer to the natural question: which of the seven invariants associated with colouring the nonempty subsets of \(\{V, E, F\}\) exhibit “asymptotically good” behaviour?

The bin packing problem has been studied extensively since the 1970’s, and it is known to be applicable to many different areas, especially in operations research and computer science. In this paper, we present a variant of the classical bin packing problem, which allows the packing to exceed its bin size but at least a fraction of the last piece is within the bin, and we call it the open-end bin packing problem. This paper is focused on on-line open-end bin packing. An on-line open-end bin packing algorithm is to assign incoming pieces into the bins on-line, that is, there is no information about the sizes of the pieces in future arrivals. An on-line algorithm is optimal if it always produces a solution with the minimum number of bins used for packing. We show that no such optimal algorithm exists. We also present seven efficient on-line algorithms: Next Fit, Random Fit, Worst Fit, Best Fit, Refined Random Fit, Refined Worst Fit, and Refined Best Fit, which give sub-optimal solutions. The performances of these algorithms are studied. A case study for the application of the studied problem is presented, and this is a practical problem on maximizing the savings of using stored-value tickets issued by Kowloon-Canton Railway (KCR), which is one of the major public transportation means in Hong Kong.