LEADER 06027nam 2200745Ia 450 001 9910450791603321 005 20200520144314.0 010 $a1-281-91178-X 010 $a9786611911782 010 $a981-277-158-1 035 $a(CKB)1000000000407517 035 $a(EBL)3050886 035 $a(OCoLC)922951739 035 $a(SSID)ssj0000127247 035 $a(PQKBManifestationID)11157322 035 $a(PQKBTitleCode)TC0000127247 035 $a(PQKBWorkID)10052084 035 $a(PQKB)10291039 035 $a(MiAaPQ)EBC3050886 035 $a(WSP)00006600 035 $a(Au-PeEL)EBL3050886 035 $a(CaPaEBR)ebr10255657 035 $a(CaONFJC)MIL191178 035 $a(EXLCZ)991000000000407517 100 $a20071016d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aComplex population dynamics$b[electronic resource] $enonlinear modeling in ecology, epidemiology, and genetics /$feditors, Bernd Blasius, Ju?rgen Kurths, Lewi Stone 210 $aSingapore ;$aHackensack, NJ $cWorld Scientific$dc2007 215 $a1 online resource (257 p.) 225 1 $aWorld Scientific lecture notes in complex systems ;$vv. 7 300 $aDescription based upon print version of record. 311 $a981-277-157-3 320 $aIncludes bibliographical references and indexes. 327 $aContents; Preface; References; 1. Chaotic dynamics in food web systems; 1.1. Introduction; 1.2. Food web model formulation; 1.3. Detecting and quantifying chaotic dynamics in model food webs; 1.4. Dynamical patterns in food webs; 1.5. Chaos in real food webs and conclusion; References; 2. Generalized models ; 2.1. Introduction; 2.2. The basic idea of generalized models; 2.3. Example: A general predator-prey system; 2.4. Additional difficulties in complex models; 2.5. A generalized spatial model; 2.6. Local stability in small and intermediate models; 2.7. Some results on global dynamics 327 $a2.8. Numerical investigation of complex networks2.9. Discussion; References; 3. Dynamics of plant communities in drylands ; 3.1. Introduction; 3.2. Model for dryland water-vegetation systems; 3.3. Landscape states; 3.3.1. Mapping the landscape states along aridity gradients; 3.3.2. Coexistence of landscape states and state transitions; 3.3.3. Landscape states and aridity classes; 3.4. Plants as ecosystem engineers; 3.4.1. Facilitation vs. resilience; 3.4.2. Facilitation vs. competition; 3.5. Species richness: Pattern formation aspects; 3.5.1. The niche concept and the niche map 327 $a3.5.2. Landscape diversity3.5.3. Environmental changes; 3.6. Conclusion; Acknowledgments; References; 4. Metapopulation dynamics and the evolution of dispersal ; 4.1. Introduction; 4.1.1. What is a metapopulation?; 4.1.2. Levins metapopulation model; 4.2. Metapopulation ecology in different models; 4.2.1. Local dynamics; 4.2.2. Finite number of patches with the Ricker model; 4.2.3. Infinite number of patches; 4.2.3.1. Model presentation; 4.2.3.2. Resident equilibrium; 4.3. Adaptive dynamics; 4.3.1. Invasion fitness; 4.3.2. Pairwise Invasibility Plots (PIP); 4.4. Evolution of dispersal 327 $a4.4.1. Finite number of patches4.4.1.1. Fitness; 4.4.1.2. Fixed-point attractor; 4.4.1.3. Cyclic orbits; 4.4.2. Infinite number of patches; 4.4.2.1. Invasion fitness for the mutant; 4.4.2.2. Results; 4.4.3. Local growth with an Allee effect can result in evolu- tionary suicide; 4.4.3.1. Local population growth with an Allee effect; 4.4.3.2. Allee effect in the metapopulation model; 4.4.3.3. Bifurcation to evolutionary suicide; 4.4.3.4. Theory of evolutionary suicide; 4.5. Summary; References; 5. The scaling law of human travel - A message from; References 327 $a6. Multiplicative processes in social systems 6.1. Introduction; 6.2. Models for Zipf's law in language; 6.3. City sizes and the distribution of languages; 6.4. Family names; 6.4.1. The effects of mortality; 6.4.2. The distribution of given names; 6.5. Conclusion; Acknowledgments; References; 7. Criticality in epidemiology ; 7.1. Introduction; 7.2. Simple epidemic models showing criticality; 7.2.1. The SIS epidemic; 7.2.2. Solution of the SIS system shows criticality; 7.2.3. The spatial SIS epidemic; 7.2.4. Dynamics for the spatial mean; 7.2.5. Moment equations; 7.2.6. Mean field behavior 327 $a7.3. Accidental pathogens: the meningococcus 330 $a"This collection of review articles is devoted to the modeling of ecological, epidemiological and evolutionary systems. Theoretical mathematical models are perhaps one of the most powerful approaches available for increasing our understanding of the complex population dynamics in these natural systems. Exciting new techniques are currently being developed to meet this challenge, such as generalized or structural modeling, adaptive dynamics or multiplicative processes. Many of these new techniques stem from the field of nonlinear dynamics and chaos theory, where even the simplest mathematical rule can generate a rich variety of dynamical behaviors that bear a strong analogy to biological populations." 410 0$aWorld Scientific lecture notes in complex systems ;$vv. 7. 606 $aPopulation biology$xMathematical models 606 $aEcology$xMathematical models 606 $aEpidemiology$xMathematical models 606 $aGenetics$xMathematical models 608 $aElectronic books. 615 0$aPopulation biology$xMathematical models. 615 0$aEcology$xMathematical models. 615 0$aEpidemiology$xMathematical models. 615 0$aGenetics$xMathematical models. 676 $a577.8/8 701 $aBlasius$b Bernd$0891171 701 $aKurths$b J$g(Ju?rgen),$f1953-$0517276 701 $aStone$b Lewi$0891172 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910450791603321 996 $aComplex population dynamics$91990499 997 $aUNINA LEADER 10363nam 2200505 450 001 996500062603316 005 20230401045440.0 010 $a3-031-18530-7 035 $a(MiAaPQ)EBC7143809 035 $a(Au-PeEL)EBL7143809 035 $a(CKB)25430587200041 035 $a(PPN)266348262 035 $a(EXLCZ)9925430587200041 100 $a20230401d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aCombinatorial optimization $e7th International Symposium, ISCO 2022, virtual event, May 18-20, 2022, revised selected papers /$fIvana Ljubic [and three others] editors 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$d©2022 215 $a1 online resource (340 pages) 225 1 $aLecture notes in computer science ;$v13526 311 08$aPrint version: Ljubi?, Ivana Combinatorial Optimization Cham : Springer International Publishing AG,c2022 9783031185298 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- Organization -- Plenary Lectures -- Graphical Designs -- Advances in Approximation Algorithms for Tree Augmentation -- Algorithmic Data Science -- Recent Algorithmic Advances for Maximum-Entropy Sampling -- Contents -- Polyhedra and Algorithms -- New Classes of Facets for Complementarity Knapsack Problems -- 1 Introduction -- 2 Notations, Assumptions, and Previous Work -- 3 Separation Complexity of Lifted Cover Inequalities for CKP -- 4 New Families of Facet-Defining Inequalities -- 5 Future Direction -- References -- Branch-and-Cut for a 2-Commodity Flow Relocation Model with Time Constraints -- 1 Introduction -- 2 A TEN Model for the Item Relocation Problem -- 3 The Projected IRP Model -- 3.1 Extended Subtour Constraints and Projected Cost -- 3.2 Separating the Extended Subtour Constraints -- 4 Algorithmic Handling and Numerical Experiments -- 4.1 Separation Algorithm -- 4.2 Numerical Experiments -- 5 Conclusion: A Brief Discussion of the Lift Issue -- References -- The Constrained-Routing and Spectrum Assignment Problem: Valid Inequalities and Branch-and-Cut Algorithm -- 1 Introduction -- 2 The Constrained-Routing and Spectrum Assignment Problem -- 3 Integer Linear Programming Formulation -- 4 Valid Inequalities and Facets -- 4.1 Edge-Capacity-Cover Inequalities -- 4.2 Edge-Interval-Capacity-Cover Inequalities -- 4.3 Edge-Interval-Clique Inequalities -- 4.4 Edge-Slot-Assignment-Clique Inequalities -- 4.5 Slot-Assignment-Clique Inequalities -- 5 Branch-and-Cut Algorithm -- 6 Computational Study -- 7 Conclusion -- References -- Polyhedra and Combinatorics -- Top-k List Aggregation: Mathematical Formulations and Polyhedral Comparisons -- 1 Introduction -- 2 Preliminaries -- 3 Integer Programming Formulations -- 4 Polyhedral Comparison -- 5 Concluding Remarks -- References -- Bounded Variation in Binary Sequences. 327 $a1 Introduction -- 2 Penalized Variation -- 3 Bounded Variation -- 4 Conclusion and Future Work -- References -- On Minimally Non-firm Binary Matrices -- 1 Introduction -- 2 Preliminaries -- 3 Simplicial 1s and Stretching -- 4 Superfirm Matrices and Odd Holes -- 5 Four Infinite Classes of Minimally Non-firm Matrices -- 6 Conclusion -- References -- Few Induced Disjoint Paths for H-Free Graphs -- 1 Introduction -- 1.1 Related Work -- 1.2 Our Results -- 2 Polynomial-Time Algorithms -- 3 Completing the Proof of Theorem 2 -- 3.1 Omitting ``H''-Graphs and Six-Vertex Cycles -- 4 Conclusions -- References -- On Permuting Some Coordinates of Polytopes -- 1 Introduction and Motivation -- 2 (More) Background and Related Work -- 2.1 Relevant Polytopes -- 3 Results -- 3.1 Parity Constraints via Partial Permutations -- 3.2 Partial Permutation over Quad-Valued Coordinates -- 3.3 Partial Permutation over Three-Valued Coordinates -- 3.4 Sorting Polytopes -- 4 Concluding Remarks -- References -- Non-linear Optimization -- Piecewise Linearization of Bivariate Nonlinear Functions: Minimizing the Number of Pieces Under a Bounded Approximation Error -- 1 Problem Description and State of the Art -- 2 Definitions -- 3 A Framework for Solving the R2-Corridor Fitting Problem -- 3.1 Key Idea 1: Management of the Corridor Domain -- 3.2 Key Idea 2: The Maximal Piece in Direction d Problem -- 3.3 Key Idea 3: Computing a Feasible Solution of a Maximal Piece in Direction d Problem -- 4 Framework Key Points Instantiation -- 4.1 Scoring the Quality of Pieces -- 4.2 Choose a Progress Direction -- 4.3 Inner Approximation of a Corridor -- 5 Numerical Experiments -- 6 Conclusion -- References -- An Outer-Approximation Algorithm for Maximum-Entropy Sampling -- 1 Introduction -- 2 Outer Approximation -- 3 Convex Relaxations for [MESP]MESP -- 4 Disjunctive Cuts -- 5 Experiments. 327 $a6 Next Steps -- References -- Mitigating Anomalies in Parallel Branch-and-Bound Based Algorithms for Mixed-Integer Nonlinear Optimization -- 1 Introduction -- 2 Anomalies in Parallel Algorithms -- 3 Opportunistic Parallel Branch-and-Bound in Minotaur -- 4 Reducing Detrimental Anomalies in Parallel NLP-BB -- 4.1 Unambiguous Branching Functions -- 4.2 Unambiguous Reliability Branching Scheme -- 4.3 A Hybrid Unambiguous Node Selection Strategy -- 4.4 Nondetrimental NLP-BB -- 5 Reducing Detrimental Anomalies in Parallel QG -- 6 Computational Results -- 7 Conclusions and Future Directions -- References -- Game Theory -- Exact Price of Anarchy for Weighted Congestion Games with Two Players -- 1 Introduction -- 2 Results -- 3 LP Based Proofs -- 4 Concluding Remarks -- References -- Nash Balanced Assignment Problem -- 1 Introduction -- 2 LP Formulation for BAP -- 3 Nash Fairness Solutions for the AP -- 3.1 Proportional Fairness -- 3.2 Characterization of NF Solutions for the AP -- 3.3 Existence of NF Solutions -- 4 Finding All NF Solutions for the AP -- 4.1 Upper Bound for the Number of NF Solutions -- 4.2 Algorithm for Finding All NF Solutions -- 4.3 Numerical Results -- 5 Conclusion -- References -- Graphs and Trees -- On the Thinness of Trees -- 1 Introduction -- 2 Definitions and Preliminaries -- 3 Characterization and Algorithm -- 3.1 The Algorithm: Rooted Trees, k-critical Vertices and Labels -- 3.2 Computing Thinness of Trees and Finding a Consistent Solution -- References -- Generating Spanning-Tree Sequences of a Fan Graph in Lexicographic Order and Ranking/Unranking Algorithms -- 1 Introduction -- 2 Preliminary -- 3 Generating Fan-Tree Sequences -- 4 Ranking and Unranking Algorithms -- 5 Concluding Remarks -- References -- Cutting and Packing -- High Multiplicity Strip Packing with Three Rectangle Types -- 1 Introduction. 327 $a2 Solving 2DFSPP in Polynomial Time -- 3 Algorithm for 2DHMSPP with Three Rectangle Types -- 3.1 Partitioning the Packing -- 3.2 Grouping Vertical Sections -- 3.3 Ordering the Configurations -- 3.4 Rounding Fractional Rectangles -- 3.5 None of SCase1, SCase2, and SCase3 are Empty, count = 1, and f1(i) + f2(i) 1 for all Vertical Sections si SCase2 -- 3.6 None of SCase1, SCase2, and SCase3 are Empty, count = 1, and f1(i) + f2(i) > -- 1 for at Least One Vertical Section si SCase2 -- 4 Polynomial Time Implementation -- 5 Conclusion -- References -- Improved Bounds for Stochastic Extensible Bin Packing Under Distributional Assumptions -- 1 Introduction -- 2 Stochastic Extensible Bin Packing -- 3 Second-Order Stochastic Dominance -- 4 Restriction to a Family of Processing Time Distributions -- References -- Applications -- One Transfer per Patient Suffices: Structural Insights About Patient-to-Room Assignment -- 1 Introduction -- 2 Every Patient Has to Be Transferred at Most Once -- 3 No Need to Transfer Patients Arriving in the First Period -- 4 Upper Bounds on the Number of Patient Transfers -- 5 Conclusion -- References -- Tool Switching Problems in the Context of Overlay Printing with Multiple Colours -- 1 Introduction -- 2 CUF-ToSP -- 2.1 Two-Index Formulation for CUF-ToSP -- 3 GOF-ToSP -- 3.1 Five-Index Arc Flow Formulation for GOF-ToSP -- 3.2 Preprocessing -- 4 GOV-ToSP -- 4.1 Six-Index Arc Flow Formulation for GOV-ToSP -- 5 Computational Results -- 5.1 Test Instances -- 5.2 Results -- 6 Conclusions and Future Research -- References -- Optimal Vaccination Strategies for Multiple Dose Vaccinations -- 1 Introduction -- 2 Problem Description and Formulation -- 3 The Matching Approach -- 3.1 Without Capacities -- 3.2 Include Upper Bound on Vaccination Speed and Storage Capacity -- 3.3 Include Multiple Vaccines and Cross-Immunization. 327 $a4 The Three-Dose Problem -- 5 Conclusion -- References -- Approximation Algorithms -- Pervasive Domination -- 1 Introduction -- 1.1 Our Model -- 1.2 Our Results -- 2 Related Work -- 3 Pervasive Partial Domination -- 3.1 Algorithm Analysis -- 4 Conclusion -- References -- Unified Greedy Approximability Beyond Submodular Maximization -- 1 Introduction -- 2 Weak Submodularity Ratio, -Augmentability, and Independence Systems -- 2.1 Separating Function Classes -- 3 -Augmentability -- 3.1 A Critical Function -- 3.2 -Augmentability on Independence Systems -- 4 Outlook -- References -- Neighborhood Persistency of the Linear Optimization Relaxation of Integer Linear Optimization -- 1 Introduction -- 2 Preliminaries -- 3 Main Results -- 4 Maximality of UTVPI Systems -- 5 Fixed-Parameter Tractability and Two-Approximability for Special Cases -- 6 Conclusion -- References -- Polynomial-Time Approximation Schemes for a Class of Integrated Network Design and Scheduling Problems with Parallel Identical Machines -- 1 Introduction and Results -- 1.1 Problem Definition -- 1.2 Our Results -- 1.3 Related Work -- 2 Proofs of Lemmas1 and 2 -- 2.1 Proof of Lemma1 -- 2.2 Proof of Lemma2 -- 3 Proofs of Corollaries1 and 2 -- 3.1 Case of {MST, SP}. -- References -- Author Index. 410 0$aLecture notes in computer science ;$v13526. 606 $aCombinatorial optimization 606 $aCombinatorial optimization$vCongresses 615 0$aCombinatorial optimization. 615 0$aCombinatorial optimization 676 $a519.64 702 $aLjubic$b Ivana 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996500062603316 996 $aCombinatorial optimization$9262324 997 $aUNISA