Polynomial algorithms for guillotine cutting of a rectangle into small rectangles of two kinds

In this paper the problem of optimally guillotine cutting a rectangle (A, B  ) into small rectangles of two kinds is considered. Rectangles of the first kind (c,_ai),i∈I$(c\text{,}{a}_i)\text{,}i\in I$ have the same width, and their heights can be various. Rectangles of the second kind (_bj,d),j∈J$(b_j\text{,}d)\text{,}j\in J$ have the same height, and their widths can be various. The number of occurrences of each small rectangle in a cutting pattern is not restricted. Similar problems often appear in the furniture industry. This cutting problem is reduced to the shortest path problem in a special rectangular grid, for which a linear time algorithm is suggested. This approach generalizes the approach of [E. Girlich, A.G. Tarnowski, On polynomial solvability of two multiprocessor scheduling problems, Mathematical Methods of Operations Research 50 (1999) 27–51; A.G. Tarnowski, Advanced polynomial time algorithm for guillotine generalized pallet loading problem, in: The International Scientific Collection: Decision Making Under Conditions of Uncertainty (Cutting-Packing Problems), Ufa State Aviation Technical University, 1997, pp. 93–124] and allows us to construct polynomial algorithms for the guillotine cutting problem considered with a fixed number of small rectangles of two kinds.     

Two explicit Skorokhod embeddings for simple symmetric random walk

Motivated by problems in behavioural finance, we provide two explicit constructions of a randomized stopping time which embeds a given centred distribution $\mu$ on integers into a simple symmetric random walk in a uniformly integrable manner. Our first construction has a simple Markovian structure: at each step, we stop if an independent coin with a state-dependent bias returns tails. Our second construction is a discrete analogue of the celebrated Azéma–Yor solution and requires independent coin tosses only when excursions away from maximum breach predefined levels. Further, this construction maximizes the distribution of the stopped running maximum among all uniformly integrable embeddings of $\mu$.     

New efficient shortest path simplex algorithm: pseudo permanent labels instead of permanent labels

We introduce a new network simplex pivot rule for the shortest path simplex algorithm. This new pivot rule chooses a subset of non-basic arcs to simultaneously enter into the basis. We call this operation a multiple pivot. We show that a shortest path simplex algorithm with this pivot rule performs O(n) multiple pivots and runs in O(nm) time. Our pivot rule is based on the new concept of a pseudo permanently labeled node, and it can be adapted to design a new label-correcting algorithm that runs in O(nm). Moreover, this concept lets us introduce new rules to identify negative cycles. Finally, we compare the network simplex algorithm with multiple pivots with other previously proposed efficient network simplex algorithm in a computational experiment.     

Efficient algorithms for the 2-Way Multi Modal Shortest Path Problem

We consider the 2-Way Multi Modal Shortest Path Problem (2WMMSPP). Its goal is to find two multi modal paths with total minimal cost, an outgoing path and a return path. The main difficulty lies in the fact that if a private car or bicycle is used during the outgoing path, it has to be picked up during the return path. The shortest return path is typically not equal to the shortest outgoing path as traffic conditions and timetables of public transportation vary throughout the day. In this paper we propose an efficient algorithm based on bi-directional search and provide experimental results on a realistic multi modal transportation network.     

On the complexity of finding paths in a two‐dimensional domain I: Shortest paths

The computational complexity of finding a shortest path in a two‐dimensional domain is studied in the Turing machine‐based computational model and in the discrete complexity theory. This problem is studied with respect to two formulations of polynomial‐time computable two‐dimensional domains: (A) domains with polynomialtime computable boundaries, and (B) polynomial‐time recognizable domains with polynomial‐time computable distance functions. It is proved that the shortest path problem has the polynomial‐space upper bound for domains of both type (A) and type (B); and it has a polynomial‐space lower bound for the domains of type (B), and has a #P lower bound for the domains of type (A). (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

On genetic algorithms for the packing of polygons

A genetic algorithm for placing polygons on a rectangular board is proposed. The algorithm is improved by combination with deterministic methods.     

Symmetry helps: Bounded bi-directional dynamic programming for the elementary shortest path problem with resource constraints

When vehicle routing problems with additional constraints, such as capacity or time windows, are solved via column generation and branch-and-price, it is common that the pricing subproblem requires the computation of a minimum cost constrained path on a graph with costs on the arcs and prizes on the vertices. A common solution technique for this problem is dynamic programming. In this paper we illustrate how the basic dynamic programming algorithm can be improved by bounded bi-directional search and we experimentally evaluate the effectiveness of the enhancement proposed. We consider as benchmark problems the elementary shortest path problems arising as pricing subproblems in branch-and-price algorithms for the capacitated vehicle routing problem, the vehicle routing problem with distribution and collection and the capacitated vehicle routing problem with time windows.     

A simple algorithm for expanding a power series as a continued fraction

I present and discuss an extremely simple algorithm for expanding a formal power series as a continued fraction. This algorithm, which goes back to Euler (1746) and Viscovatov (1805), deserves to be better known. I also discuss the connection of this algorithm with the work of Gauss (1812), Stieltjes (1889), Rogers (1907) and Ramanujan, and a combinatorial interpretation based on the work of Flajolet (1980).     

Internet packet routing: Application of a K-quickest path algorithm

This paper describes a study on the application of an algorithm to rank the K-quickest paths to the routing of data packets in Internet networks. For this purpose an experimental framework was developed by considering two types of random generated networks. To simulate values of the IP packet sizes, a truncated Pareto distribution was defined, having in mind to reflect a key feature of Internet traffic, namely its self-similar stochastic nature. Results concerning the average CPU times of the algorithm for the different sets of experiments will be presented and discussed.     

Auction algorithms for network flow problems: A tutorial introduction

This paper surveys a new and comprehensive class of algorithms for solving the classical linear network flow problem and its various special cases such as shortest path, max-flow, assignment, transportation, and transhipment problems. The prototype method, from which the other algorithms can be derived, is the auction algorithm for the assignment problem. This is an intuitive method that operates like a rel auction where persons compete for objects by raising their prices through competitive bidding; the prices can be viewed as dual variables. Conceptually, auction algorithms represent a significant departure from the cost improvement idea that underlies primal simplex and dual ascent methods; at any one iteration, they may deteriorate both the primal and the dual cost. Auction algorithms perform very well for several important types of problems, both in theory and in practice, and they are also well suited for parallel computation.