It is known that under a plausible assumption on the class N P the greedy algorithm is close to best approximate polynomial algorithms for the set cover problem solving. Unfortunately, the performance ratio of this algorithm grows almost as natural logarithm on the cardinality of covered set. ...
accelerates algorithm convergence, enhances optimization precision, and prevents the algorithm from falling into local convergence. Finally, implementing a scouting bee strategy, where whale individuals progressively increase the number of optimization failures within a limited parameterL. When a threshold is ...
Many real-world engineering problems need to balance different objectives and can be formatted as multi-objective optimization problem. An effective multi-objective algorithm can achieve a set of optimal solutions that can make a tradeoff between differe
Naderi, B., Rahmani, S., Rahman, S.: A Multiobjective Iterated Greedy Algorithm for Truck Scheduling in Cross-Dock Problems. Journal of Industrial Engineering, Article ID 128542, 12 pages (2014)Naderi, B., Rahmani, S., Rahman, S.: A Multiobjective Iterated Greedy Algorithm for Truck ...
This repository contains the solutions and explanations to the algorithm problems on LeetCode. Only medium or above are included. All are written in C++/Python and implemented by myself. The problems attempted multiple times are labelled with hyperlinks.
Guo et al.50 utilized crossing and mutating techniques to update particles, and an improved particle swarm algorithm was proposed for air combat decision-making. Niu et al. introduced a maximum team performance optimization method to allocate targets.51 Based on greedy algorithm and ant colony ...
Greedy Greedy Algorithm to find Minimum number of Coins <-> Greedy Maximum trains for which stoppage can be provided <-> Greedy Minimum Platforms Problem <-> Greedy Buy Maximum Stocks if i stocks can be bought on i-th day <-> Greedy Find the minimum and maximum amount to buy all N can...
Iterated Greedy (IG) algorithm is a simple but very effective algorithm that has demonstrated state-of-the-art performance for many different flowshop problems and variants [17]. Unlike methods based on complex metaphors, IG is just an iterative search method with no memory and few structures. ...
Based on this information (and on many other constraints), the department then assigns courses to students. Until recently, the assignment was computed by human schedulers who used a quite straightforward greedy approach. In 2005, however, the number of students increased substantially, and as a ...
Chumburidze M, Basheleishvili I, Khetsuriani A (2019) Dynamic programming and greedy algorithm strategy for solving several classes of graph optimization problems. BRAIN. Broad Res Artif Intell Neurosci 10(1):101–107 Google Scholar Lan G (2020) First-order and stochastic optimization methods...