Algorithm算法代写代考

代写 algorithm COMP90038 Algorithms and Complexity

COMP90038 Algorithms and Complexity Lecture 15: Balanced Trees (with thanks to Harald Søndergaard & Michael Kirley) Andres Munoz-Acosta munoz.m@unimelb.edu.au Peter Hall Building G.83 Recap • Last week we talked about: • Two representations: Heaps and Binary Search Trees • An algorithm: Heapsort • An strategy: Transform-and-conquer through pre-sorting Differences between heaps and BSTs • We […]

代写 algorithm COMP90038 Algorithms and Complexity Read More »

代写 algorithm COMP90038 Algorithms and Complexity

COMP90038 Algorithms and Complexity Lecture 14: Transform and Conquer (with thanks to Harald Søndergaard & Michael Kirley) Andres Munoz-Acosta munoz.m@unimelb.edu.au Peter Hall Building G.83 Exercise: Finding Anagrams • An anagram of a word w is a word which uses the same letters as w but in a different order. • Example: ‘ate’, ‘tea’ and ‘eat’

代写 algorithm COMP90038 Algorithms and Complexity Read More »

代写 algorithm 问题概述

问题概述 卫星仓库管理在电商配送最后一公里中的应用 如今,由于电子商务不断发展,客户的购买行为变化多端,所以城市配送必 须应对这些变化。事实上, 客户期待所购商品的配送速度更快(通常时间极其有限, 在 2小时内)、配送费更低。他们可以联系配送、掌握相关情况并拥有权利, 还可 以要求交货方式更多,更加灵活。 为满足这些要求并提高服务速度, 企业和电子商务巨头平台正推广由成本驱 动转向时间和成本共同驱动的方法 (即需求驱动的物流), 这完全改变了物流链。 这种方法使需求通过将产品拉入位于城区附近的双层配送中心来协调供应 链, 从而形成所谓的双层配送系统 (图 1)。城市整合中心(UCCs)是位于城市战略 节点上的物流平台, 代表该系统的第一级,而卫星则构成了第二级,来自城市整合 中心和其他外来货物会在此被转运整合到适用于城市密集区的车辆上 (如电动 车)。 此外,人们对提高交货速度的需求日益强烈, 为满足该需求,众包配送 (也称 为最后一公里的“优步化”) 在城市配送中越来越受欢迎。这种模式指的是要求当 地非专职司机管理送货, 有时不到一个小时即可送达。通常,一旦接到订单, 就 会根据非专业兼职快递员的拿货位置, 使用移动应用程序进行货物分配。最后, 指派的快递人使用其车辆将包裹送到买家手中。 图一—双层配送系统 (Crainic 和Sgalambro, 2014) 1 上述系统是一个多方参与的复杂系统, 参与者包括快递公司、卫星管理者、地方 管理部门,他们都有自己的目标。 • 快递公司的目标是最大限度地降低交货成本, 包括车辆成本和租用仓库 的关税。 • 卫星管理人员希望从社会和环境方面部署策略,以有效利用卫星仓库的 承载量。 • 最后, 市政府的目标是保证城市内基础设施得到有效使用, 鼓励采取措施 作为定价策略,

代写 algorithm 问题概述 Read More »

代写 algorithm School of Computing and Information Systems COMP90038 Algorithms and Complexity Tutorial Week 10

School of Computing and Information Systems COMP90038 Algorithms and Complexity Tutorial Week 10 Sample Answers The exercises 67. Use Horspool’s algorithm to search for the pattern GORE in the string ALGORITHM. Answer: For that pattern we calculate the shifts: S[G] = 3,S[O] = 2,S[R] = 1,S[x] = 4 for all other letters x. So the

代写 algorithm School of Computing and Information Systems COMP90038 Algorithms and Complexity Tutorial Week 10 Read More »

代写 C algorithm html COMP90038 Algorithms and Complexity

COMP90038 Algorithms and Complexity Lecture 16: Time/Space Tradeoffs – String Search Revisited (with thanks to Harald Søndergaard & Michael Kirley) Andres Munoz-Acosta munoz.m@unimelb.edu.au Peter Hall Building G.83 Recap • BST have optimal performance when they are balanced. • AVL Trees: • Self-balancing trees for which the balance factor is -1, 0, or 1, for every

代写 C algorithm html COMP90038 Algorithms and Complexity Read More »

代写 C data structure algorithm The University of Melbourne

The University of Melbourne School of Computing and Information Systems COMP90038 Algorithms and Complexity Assignment 2, Semester 2, 2018 Released: Tuesday 25 September. Deadline: Sunday 14 October at 23:59 Ob jectives To improve your understanding of data structures and algorithms for sorting and search. To consolidate your knowledge of trees and tree-based algorithms. To develop

代写 C data structure algorithm The University of Melbourne Read More »

代写 algorithm math graph Plan

Plan School of Computing and Information Systems COMP90038 Algorithms and Complexity Tutorial Week 3 6–10 August 2018 Last week’s lecture discussed asymptotics and the mathematical analysis of algorithms; this week’s lectures will be about brute force methods and recursion. This week’s questions 12–14 are combinatorics-style puzzles. Good problem-solving fun, but not essential. The exercises 7.

代写 algorithm math graph Plan Read More »

代写 R C data structure algorithm math compiler statistic COMP90038 Algorithms and Complexity

COMP90038 Algorithms and Complexity Lecture 17: Hashing (with thanks to Harald Søndergaard & Michael Kirley) Andres Munoz-Acosta munoz.m@unimelb.edu.au Peter Hall Building G.83 Recap • We talked about using some memory space (in the form of extra tables, arrays, etc.) to speed up our computation. • Memory is cheap, time is not. • Sorting by counting

代写 R C data structure algorithm math compiler statistic COMP90038 Algorithms and Complexity Read More »