图的割宽最大值问题

§ 1　IntroductionThe cutwidth minimization problem for graphs arises from the circuitlayout of VLSIdesigns[1 ] .Chung pointed outthatthe cutwidth often corresponds to the area of the layoutin array layout in VLSI design[2 ] .In the layout models,the cutwidth problem deals withthe number of edges passing over a vertex when all vertices are arranged in a path.For agraph G with vertex set V(G) and edge set E(G) ,a labeling of G is a one-to-one mapping ffrom V(G) to the integers.The cutwid…     

Minimal cutwidth linear arrangements of abelian Cayley graphs

We find the minimal cutwidth and bisection width values for abelian Cayley graphs with up to 4 generators and present an algorithm for finding the corresponding optimal ordering. We also find minimal cuts of each order.     

图的割宽总是的度序列方法

The cutwidth problem for a graph G is to embed G into a path such that the maximum number of overlap edges is minimized. This paper presents an approach based on the degree sequence of G for determining the exact value of cutwidth of typical graphs (e. g. , n-cube,cater-pillars). Relations between the cutwidth and other graph-theoretic parameters are studied as well.     

Decentralized operation strategies for an integrated building energy system using a memetic algorithm

The emerging technology in net-zero building and smart grids drives research moving from centralized operation decisions on a single building to decentralized decisions on a group of buildings, termed a building cluster which shares energy resources locally and globally. However, current research has focused on developing an accurate simulation of single building energy usage which limits its application to building clusters as scenarios such as energy sharing and competition cannot be modeled and studied. We hypothesize that the study of energy usage for a group of buildings instead of one single building will result in a cost effective building system which in turn will be resilient to power disruption. To this end, this paper develops a decision model based on a building cluster simulator with each building modeled by energy consumption, storage and generation sub modules. Assuming each building is interested in minimizing its energy cost, a bi-level operation decision framework based on a memetic algorithm is proposed to study the tradeoff in energy usage among the group of buildings. Two additional metrics, measuring the comfort level and the degree of dependencies on the power grid are introduced for the analysis. The experimental result demonstrates that the proposed framework is capable of deriving the Pareto solutions for the building cluster in a decentralized manner. The Pareto solutions not only enable multiple dimensional tradeoff analysis, but also provide valuable insight for determining pricing mechanisms and power grid capacity.     

A memetic algorithm for job shop scheduling using a critical-path-based local search heuristic

In this article, a new memetic algorithm has been proposed to solve job shop scheduling problems (JSSPs). The proposed method is a genetic-algorithm-based approach combined with a local search heuristic. The proposed local search heuristic is based on critical operations. It removes the critical operations and reassigns them to a new position to improve the fitness value of the schedule. Moreover, in this article, a new fitness function is introduced for JSSPs. The new fitness function called priority-based fitness function is defined in three priority levels to improve the selection procedure. To show the generality of our proposed method, we apply it to three different types of job scheduling problems including classical, flexible and multi-objective flexible JSSPs. The experiment results show the efficiency of the proposed fitness function. In addition, the results show that incorporating local search not only offers better solutions but also improves the convergence rate. Compared to the state-of-the-art algorithms, the proposed method outperforms the existing methods in classical JSSPs and offers competitive solutions in other types of scheduling problems.     

Minimizing weighted tardiness of job-shop scheduling using a hybrid genetic algorithm

Relative to job-shop scheduling problems that optimize makespan or flow time, due-date-related problems are usually much more computationally complex and are classified as strongly NP-hard. In this paper, a hybrid framework integrating a heuristic and a genetic algorithm (GA) is utilized for job-shop scheduling to minimize weighted tardiness. For each new generation of schedules, the GA determines the first operation of each machine, and the heuristic determines the assignment of the remaining operations. Schedules with inferior tardiness are discarded before the next round of evolution. Extensive numerical experiments were conducted for different levels of due-date tightness. The results show that the hybrid framework performs significantly better than does either a heuristic or GA alone. It is also found to be superior to a well-recognized heuristic improvement procedure (lead-time iterations). Specifically, the combination of the R&M heuristic and a GA outperforms a number of heuristics commonly used to minimize total tardiness and weighted total tardiness; this combination is, however, outperformed by the heuristic of Kreipl [Kreipl, S., 2000. A large step random walk for minimizing total weighted tardiness in a job shop. Journal of Scheduling 3, 125–138]. We also develop a generalized hybrid framework that can adapt to different job-shop problems—with or without sequence-dependent setups and with different objectives (e.g., makespan, tardiness, flow time). The new framework allows the interaction of parallel evolutions, extending the GA-heuristic environment to the solving of multi-objective scheduling problems.     

A memetic algorithm for graph coloring

Given an undirected graph G=(V,E)$G=(V\text{,}E)$ with a set V of vertices and a set E of edges, the graph coloring problem consists of partitioning all vertices into k independent sets and the number of used colors k is minimized. This paper presents a memetic algorithm (denoted by MACOL) for solving the problem of graph coloring. The proposed MACOL algorithm integrates several distinguished features such as an adaptive multi-parent crossover (AMPaX) operator and a distance-and-quality based replacement criterion for pool updating. The proposed algorithm is evaluated on the DIMACS challenge benchmarks and computational results show that the proposed MACOL algorithm achieves highly competitive results, compared with 11 state-of-the-art algorithms. The influence of some ingredients of MACOL on its performance is also analyzed.     

Enumeration of cyclic graphs and cyclic designs

The close relationship of cyclic graphs and cyclic designs is pointed out and used in the enumeration of cyclic graphs. An explicit formula is given for graphs with a prime number of vertices and a general constructive method of enumeration is developed. The problem is shown to be the same as that of enumerating cyclic paired-comparison designs which was previously considered by the author. The earlier results are extended and modified.     

On a cyclic connectivity property of directed graphs

Let us call a digraph D cycle-connected if for every pair of vertices u,v∈V(D) there exists a cycle containing both u and v. In this paper we study the following open problem introduced by Ádám. Let D be a cycle-connected digraph. Does there exist a universal edge in D, i.e., an edge e∈E(D) such that for every w∈V(D) there exists a cycle C such that w∈V(C) and e∈E(C)?In his 2001 paper Hetyei conjectured that cycle-connectivity always implies the existence of a universal edge. In the present paper we prove the conjecture of Hetyei for bitournaments.     

A memetic algorithm for multi-objective dynamic location problems

This paper describes a new multiobjective interactive memetic algorithm applied to dynamic location problems. The memetic algorithm integrates genetic procedures and local search. It is able to solve capacitated and uncapacitated multi-objective single or multi-level dynamic location problems. These problems are characterized by explicitly considering the possibility of a facility being open, closed and reopen more than once during the planning horizon. It is possible to distinguish the opening and reopening periods, assigning them different coefficient values in the objective functions. The algorithm is part of an interactive procedure that asks the decision maker to define interesting search areas by establishing limits to the objective function values or by indicating reference points. The procedure will be applied to some illustrative location problems.     

A memetic algorithm for the team orienteering problem

The team orienteering problem (TOP) is a generalization of the orienteering problem. A limited number of vehicles is available to visit customers from a potential set. Each vehicle has a predefined running-time limit, and each customer has a fixed associated profit. The aim of the TOP is to maximize the total collected profit. In this paper we propose a simple hybrid genetic algorithm using new algorithms dedicated to the specific scope of the TOP: an Optimal Split procedure for chromosome evaluation and local search techniques for mutation. We have called this hybrid method a memetic algorithm for the TOP. Computational experiments conducted on standard benchmark instances clearly show our method to be highly competitive with existing ones, yielding new improved solutions in at least 5 instances.     

Compact cyclic edge-colorings of graphs

The paper is devoted to a model of compact cyclic edge-coloring of graphs. This variant of edge-coloring finds its applications in modeling schedules in production systems, in which production proceeds in a cyclic way. We point out optimal colorings for some graph classes and we construct graphs which cannot be colored in a compact cyclic manner. Moreover, we prove some theoretical properties of considered coloring model such as upper bounds on the number of colors in optimal compact cyclic coloring.     

Stratified prototype selection based on a steady-state memetic algorithm: a study of scalability

Prototype selection (PS) is a suitable data reduction process for refining the training set of a data mining algorithm. Performing PS processes over existing datasets can sometimes be an inefficient task, especially as the size of the problem increases. However, in recent years some techniques have been developed to avoid the drawbacks that appeared due to the lack of scalability of the classical PS approaches. One of these techniques is known as stratification. In this study, we test the combination of stratification with a previously published steady-state memetic algorithm for PS in various problems, ranging from 50,000 to more than 1 million instances. We perform a comparison with some well-known PS methods, and make a deep study of the effects of stratification in the behavior of the selected method, focused on its time complexity, accuracy and convergence capabilities. Furthermore, the trade-off between accuracy and efficiency of the proposed combination is analyzed, concluding that it is a very suitable option to perform PS tasks when the size of the problem exceeds the capabilities of the classical PS methods.     

Minimizing and maximizing the diameter in orientations of graphs

For a graph G, letG′(G″) denote an orientation ofG having maximum (minimum respectively) finite diameter. We show that the length of the longest path in any 2-edge connected (undirected) graph G is precisely diam(G′). LetK(m _l ,m ₂,...,m _n) be the completen-partite graph with parts of cardinalitiesm ₁ m₂, …,m _n . We prove that ifm ₁ = m₂ = … =m _n = m,n ≥ 3, then diam(K″(m₁,m₂,...,m_n)) = 2, unless m=1 andn = 4.     

A memetic algorithm for the inventory routing problem

Journal of Heuristics - In this article, we study an Inventory Routing Problem with deterministic customer demand in a two-tier supply chain. The supply chain network consists of a supplier using a...     

Analysis for optimal pattern synthesis of time modulated concentric circular antenna array using memetic firefly algorithm

In this paper the optimal performance of time modulated nine-ring concentric circular antenna array with isotropic elements has been studied based on an evolutionary optimization algorithm hybridized with local heuristic search called memetic firefly algorithm (MFA). The firefly algorithm has been applied followed by Nelder–Mead simplex method for the local heuristic search to achieve the optimal fine tuning. Other algorithms like real coded genetic algorithm (RGA) and particle swarm optimization (PSO) have been used for the comparison purpose. The comparisons among the algorithms have been made with two case studies as Case-1 and Case-2, and with two different fitness functions \((f_{{ fitness}1}, f_{{ fitness}2})\) and three control parameters like inter-element uniform/non-uniform spacing in rings, inter-ring radii and the switching-on times of rings. The simulation results show that the MFA outperforms RGA and PSO for both the cases Case-1, Case-2 and \(f_{{ fitness}1}\), \(f_{{ fitness}2}\), respectively with respect to better side lobe level (SLL). The fitness function \(f_{{ fitness}2}\) is better than the \(f_{{ fitness}1}\) with respect to sideband level. Apart from this, powers radiated at the centre/fundamental frequency and the first two sideband frequencies, and dynamic efficiency have been computed. It is found that power radiated by any sideband frequency is much less as compared to the power radiated at the centre frequency. It has been observed that as the sideband frequency increases, SBL decreases to the greater extent as compared to SLL. As per authors’ knowledge there is a little research contribution by any other previous researcher regarding numerical computation of radiation characteristics as SBLs, powers radiated at the fundamental frequency and its two sideband frequencies, directivity, and dynamic efficiency for time-modulated CCAA.     

A memetic algorithm for the virtual network mapping problem

The Internet has ossified. It has lost its capability to adapt as requirements change. A promising technique to solve this problem is the introduction of network virtualization. Instead of directly using a single physical network, working just well enough for a limited range of applications, multiple virtual networks are embedded on demand into the physical network, each of them perfectly adapted to a specific application class. The challenge lies in mapping the different virtual networks with all the resources they require into the available physical network, which is the core of the virtual network mapping problem. In this work, we introduce a memetic algorithm that significantly outperforms the previously best algorithms for this problem. We also offer an analysis of the influence of different problem representations and in particular the implementation of a uniform crossover for the grouping genetic algorithm that may also be interesting outside of the virtual network mapping domain. Furthermore, we study the influence of different hybridization techniques and the behaviour of the developed algorithm in an online setting.     

Minimizing the number of independent sets in triangle-free regular graphs

Recently, Davies, Jenssen, Perkins, and Roberts gave a very nice proof of the result (due, in various parts, to Kahn, Galvin–Tetali, and Zhao) that the independence polynomial of a $d$-regular graph is maximized by disjoint copies of $K_{d,d}$. Their proof uses linear programming bounds on the distribution of a cleverly chosen random variable. In this paper, we use this method to give lower bounds on the independence polynomial of regular graphs. We also give a new bound on the number of independent sets in triangle-free cubic graphs.     

On cyclic edge-connectivity of transitive graphs

A cyclic edge-cut of a graph G is an edge set, the removal of which separates two cycles. If G has a cyclic edge-cut, then it is said to be cyclically separable. For a cyclically separable graph G, the cyclic edge-connectivity cλ(G) is the cardinality of a minimum cyclic edge-cut of G. In this paper, we first prove that for any cyclically separable graph G, , where ω(X) is the number of edges with one end in X and the other end in V(G)?X. A cyclically separable graph G with cλ(G)=ζ(G) is said to be cyclically optimal. The main results in this paper are: any connected k-regular vertex-transitive graph with k≥4 and girth at least 5 is cyclically optimal; any connected edge-transitive graph with minimum degree at least 4 and order at least 6 is cyclically optimal.     

Minimizing the least eigenvalue of unicyclic graphs with fixed diameter

Let U(n,d) be the set of unicyclic graphs on n vertices with diameter d. In this article, we determine the unique graph with minimal least eigenvalue among all graphs in U(n,d). It is found that the extremal graph is different from that for the corresponding problem on maximal eigenvalue as done by Liu et al. [H.Q. Liu, M. Lu, F. Tian, On the spectral radius of unicyclic graphs with fixed diameter, Linear Algebra Appl. 420 (2007) 449-457].