A Heuristic Algorithm for Optimizing Business Matchmaking Scheduling

2012 ◽  
Vol 3 (4) ◽  
pp. 59-73 ◽  
Author(s):  
Yingping Huang ◽  
Xihui Zhang ◽  
Paulette S. Alexander
Keyword(s):  
Heuristic Algorithm ◽  
Small Businesses ◽  
Real Data ◽  
Government Agencies ◽  
Scheduling Problem ◽  
Maximum Cardinality ◽  
Simulation Experiments ◽  
Matching Problems ◽  
3 Dimensional ◽  
Planar Assignment Problem

Business matchmaking is a service dedicated to providing one-on-one appointments for small businesses (or sellers) to meet with government agencies and large corporations (or buyers) for contracting opportunities. Business matchmaking scheduling seeks to maximize the total number of appointments with the maximum objective that weighs the preferences of both buyers and sellers. In this paper, the authors transformed the business matchmaking scheduling problem into a 3-dimensional planar assignment problem and solved it heuristically using a series of bipartite maximum weighted maximum cardinality matching problems. Simulation experiments and real data showed that this algorithm outperforms human experts and prior algorithm in terms of number of appointments, the objective that weighs buyer and seller’s preferences, and the execution time.

The Research of Heuristic Algorithm for Flow Shop Scheduling Problem

2012 ◽  
Vol 605-607 ◽  
pp. 528-531
Author(s):  
Dan Tang ◽  
Hong Ping Shu
Keyword(s):  
Heuristic Algorithm ◽  
Processing Time ◽  
Flow Shop ◽  
Heuristic Method ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Average Quality ◽  
Simulation Experiments ◽  
Shop Scheduling ◽  
Better Than

For the flow shop scheduling problem which aims to minimize makespan, this paper gives a new derivation about its mathematical definition, and mining characteristics of the problem itself further. By which analysis, the new heuristic method proposed in the paper shorten the waiting time of each job as much as possible on the basis of reduce the processing time of the first machine and last job. The result of simulation experiments shows that, our new heuristic algorithm has good performance, and the average quality and stability of scheduling sequences generated by new method is significantly better than other heuristic algorithm which has the same complexity.

Assessment of small businesses activities in Ukraine

2019 ◽  
pp. 40-47
Author(s):  
Igor Ponomarenko ◽  
Kateryna Volovnenko
Keyword(s):  
Comparative Analysis ◽  
Statistical Analysis ◽  
Small Business ◽  
Small Businesses ◽  
Government Agencies ◽  
Small Enterprises ◽  
The Subject ◽  
Business Entities ◽  
The Impact ◽  
Micro Enterprises

The subject of the research is a set of approaches to the statistical analysis ofthe activities of small business entities in Ukraine, including micro-enterprises. The purpose of writing this article is to study of the features of functioningof small business entities in Ukraine. Methodology. The research methodology isto use a system-structural and comparative analysis (to study the change in thenumber of small enterprises by major components); monographic (when studyingmethods of statistical analysis of small businesses); economic analysis (when assessing the impact of small business entities on socio-economic phenomena andprocesses in Ukraine). The scientific novelty consists to determine the features ofthe functioning of small businesses in Ukraine in modern conditions. The influenceof the activities of the main socio-economic and political indicators on the activities of small enterprises in recent periods of time has been identified. It has beenestablished that there is flexibility in the development of strategies by small businesses in conditions of significant competition, which makes it possible to quicklyrespond to changing situations in specific markets. Conclusions. The use of acomprehensive statistical analysis of small businesses functioning in Ukraine willallow government agencies to develop a set of measures to optimize the activitiesof these enterprises, which ultimately will positively affect the strengthening oftheir competitiveness and will contribute to the growth of the national economicsystem.

scholarly journals A simulated annealing-based algorithm for selecting balanced samples

2021 ◽  
Author(s):  
Roberto Benedetti ◽  
Maria Michela Dickson ◽  
Giuseppe Espa ◽  
Francesco Pantalone ◽  
Federica Piersimoni
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Sample Selection ◽  
Auxiliary Information ◽  
Real Data ◽  
Simulation Experiments ◽  
Balanced Sampling ◽  
Inclusion Probabilities ◽  
Random Method ◽  
Annealing Algorithms

AbstractBalanced sampling is a random method for sample selection, the use of which is preferable when auxiliary information is available for all units of a population. However, implementing balanced sampling can be a challenging task, and this is due in part to the computational efforts required and the necessity to respect balancing constraints and inclusion probabilities. In the present paper, a new algorithm for selecting balanced samples is proposed. This method is inspired by simulated annealing algorithms, as a balanced sample selection can be interpreted as an optimization problem. A set of simulation experiments and an example using real data shows the efficiency and the accuracy of the proposed algorithm.

scholarly journals Improved Hybrid Heuristic Algorithm Inspired by Tissue-Like Membrane System to Solve Job Shop Scheduling Problem

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 219
Author(s):  
Xiang Tian ◽  
Xiyu Liu
Keyword(s):  
Local Search ◽  
Heuristic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Membrane System ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Hybrid Heuristic ◽  
Shop Scheduling ◽  
Hybrid Heuristic Algorithm

In real industrial engineering, job shop scheduling problem (JSSP) is considered to be one of the most difficult and tricky non-deterministic polynomial-time (NP)-hard problems. This study proposes a new hybrid heuristic algorithm for solving JSSP inspired by the tissue-like membrane system. The framework of the proposed algorithm incorporates improved genetic algorithms (GA), modified rumor particle swarm optimization (PSO), and fine-grained local search methods (LSM). To effectively alleviate the premature convergence of GA, the improved GA uses adaptive crossover and mutation probabilities. Taking into account the improvement of the diversity of the population, the rumor PSO is discretized to interactively optimize the population. In addition, a local search operator incorporating critical path recognition is designed to enhance the local search ability of the population. Experiment with 24 benchmark instances show that the proposed algorithm outperforms other latest comparative algorithms, and hybrid optimization strategies that complement each other in performance can better break through the original limitations of the single meta-heuristic method.

Linear Rail Space Dynamic Scheduling Technology for Multi-Tasking Hybrid Assembly Sections

2012 ◽  
Vol 271-272 ◽  
pp. 650-656
Author(s):  
Zhi Bing Lu ◽  
Ai Min Wang ◽  
Cheng Tong Tang ◽  
Jing Sheng Li
Keyword(s):  
Production Scheduling ◽  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Real Data ◽  
Utilization Rate ◽  
Filter Method ◽  
Scheduling Problem ◽  
Rule Based ◽  
Comprehensive Utilization ◽  
Space Production

For the rapid response to production scheduling problem driven by high-density production tasks, a dynamic scheduling technology for the large precision strip products assembly with a mixture of task time nodes and line-rail space is proposed. A scheduling constrained model containing coverage, proximity, timeliness and resource is established. A linear rail space production scheduling technology using heuristic automatic scheduling and event-driven method is put forward. The time rule based on delivery and single completion assembly is formed, at the same time the space rule based on the adjacent rail and comprehensive utilization is researched. Supposing the privilege of single product assembling as the core, the scheduling parts filter method based on multiple constraints and former rules. For the space layout problem, a clingy forward and backward algorithms is proposed to judge the assemble position regarding the space comprehensive utilization rate. The classification of the various disturbances in the actual production is summarized. Three basic algorithms are proposed, including insertion, moving and re-scheduling algorithm, in order to solve the assembly dynamic scheduling problem driven by production disturbance events. Finally, take rocket as the example， the rocket assembly space production scheduling system is developed, combining with the proposed algorithm. The practicability of the system is validated using real data.

Sign in / Sign up

Export Citation Format

Share Document