公开(公告)号：US20190080271A1

公开(公告)日：2019-03-14

申请号：US16127350

申请日：2018-09-11

Applicant: Hefei University of Technology

Inventor： Jun PEI ,  Qingru SONG ,  Xinbao LIU ,  Shaojun LU ,  Qiang ZHANG ,  Wenjuan FAN ,  Min KONG

IPC: G06Q10/06 ,  G06F7/58 ,  G06F17/30

Abstract: The present invention discloses a coordinated production and transportation scheduling method and system based on an improved tabu search algorithm, and a storage medium. The method includes batching jobs, initializing algorithm parameters, generating an initial solution, generating a neighborhood solution set, performing mutation, crossover and selection on individuals, determining a candidate solution set; calculating a fitness value of an individual, updating the candidate solution set; updating a tabu list, and determining whether an algorithm termination condition is satisfied; if yes, outputting the global optimal solution; otherwise, returning to the step 4. The present invention is mainly aimed at the coordinated production and transportation batch scheduling problem with multiple manufacturers. The whole profit of an enterprise in the production and transportation phases can be maximized, and high quality services can be provided for customers of the enterprise with improved core competitiveness of the enterprise.

公开(公告)号：US20190080244A1

公开(公告)日：2019-03-14

申请号：US16127361

申请日：2018-09-11

Applicant: Hefei University of Technology

Inventor： Jun PEI ,  Qingru SONG ,  Xinbao LIU ,  Shaojun LU ,  Qiang ZHANG ,  Wenjuan FAN

IPC: G06N3/12 ,  G06F7/58 ,  G06Q10/06

Abstract: The present invention relates to a production batch scheduling method and system based on improved variable neighborhood search and differential evolution algorithms as well as a storage medium. The method is executed by a computer, and includes: setting algorithm parameters; building a neighborhood structure; initializing a population; determining an initial solution; calculating a fitness value; locally searching; selecting a male parent; performing individual recessive variation; regenerating the population; updating the initial solution; updating a neighborhood structure of algorithmic search; and judging whether a terminal condition of algorithm execution is met, outputting a global optimal solution of the algorithmic search if so, otherwise, returning to Step 6. The present invention can obtain an approximate optimal solution in regard to a coordinated batch scheduling problem of production and transportation in the case of a manufacturer single machine based on a differential workpiece.

公开(公告)号：US20190079975A1

公开(公告)日：2019-03-14

申请号：US16127337

申请日：2018-09-11

Applicant: Hefei University of Technology

Inventor： Jun PEI ,  Wenjuan FAN ,  Xinbao LIU ,  Qiang ZHANG ,  Min KONG ,  Shaojun LU

IPC: G06F17/30 ,  G06F9/48

CPC classification number: G06F16/24542 ,  G06F9/4881 ,  Y02P90/30

Abstract: The present invention discloses a scheduling method and system based on a hybrid variable neighborhood search and gravitational search algorithm. The method includes: 1 setting parameters of the algorithm; 2 initializing an initial solution of the algorithm; 3 performing local search based on a gravitational search algorithm (GSA); 4 updating the initial solution; 5 determining whether an algorithm termination condition is satisfied; if yes, outputting the global optimal solution searched for by the algorithm, otherwise, returning to the step 3. According to the present invention, a near-optimal solution for the continuous batch processing problem based on position learning effect and linear starting time can be obtained, so that an enterprise can make full use of production resources thereof to the utmost extent, and thus reduce production costs and improve the enterprise service level and the customer satisfaction level.

公开(公告)号：US20180357584A1

公开(公告)日：2018-12-13

申请号：US16006769

申请日：2018-06-12

Applicant: Hefei University of Technology

Inventor： Xinbao LIU ,  Jun PEI ,  Mei XUE ,  Shaojun LU ,  Hao CHENG ,  Min KONG ,  Zhiping ZHOU ,  Lu JIANG

IPC: G06Q10/06 ,  G06Q10/08

CPC classification number: G06Q10/06311 ,  G06Q10/083

Abstract: The present invention discloses a method and system for collaborative scheduling of production and transportation in supply chains based on improved particle swarm optimization. The method includes the following steps: 1. setting algorithm parameters; 2. randomly generating an initial population; 3. correcting codes; 4. calculating fitness values and updating the speed and the position of particles; 5. performing tournament selection; 6. performing crossover mutation; 7. updating the population; and 8. determining whether a termination condition is satisfied; if so, outputting a globally optimal solution; if not, returning to the step 3. In the present invention, an approximately optimal solution can be obtained in view of the collaborative scheduling problem of production and transportation considering distributed storage, so that the cost is reduced for supply chains and the service level of supply chains is enhanced.

公开(公告)号：US20180357610A1

公开(公告)日：2018-12-13

申请号：US16006694

申请日：2018-06-12

Applicant: Hefei University of Technology

Inventor： Xinbao LIU ,  Jun PEI ,  Min KONG ,  Zhanhui WEI ,  Shaojun LU ,  Qingru SONG ,  Xiaofei QIAN

IPC: G06Q10/10 ,  G06Q10/08

CPC classification number: G06Q10/1093 ,  G06F7/58 ,  G06Q10/083

Abstract: A method and system for collaborative scheduling of production and transportation based on shuffled frog leaping and path relinking algorithms. The method includes the following steps: 1. setting algorithm parameters; 2. generating an initial population; 3. calculating fitness values; 4. grouping the population; 5. performing local search on all groups and updating individuals in groups; 6. performing global search on all groups and updating individuals in groups; 7. gathering all groups to obtain a new population; 8. performing a greedy path relinking algorithm on elegant solutions in the population to obtain an updated population; and, 9. determining termination conditions of algorithms; if so, ending; or otherwise, returning to the step 3.

公开(公告)号：US20180356803A1

公开(公告)日：2018-12-13

申请号：US16006743

申请日：2018-06-12

Applicant: Hefei University of Technology

Inventor： Xinbao LIU ,  Jun PEI ,  Lu JIANG ,  Shaojun LU ,  Min KONG ,  Xiaofei QIAN ,  Zhiping ZHOU ,  Mei XUE

IPC: G05B19/418 ,  G06N3/12 ,  G06Q10/04 ,  G06Q50/04

CPC classification number: G05B19/41865 ,  G05B2219/32091 ,  G05B2219/39167 ,  G06N3/126 ,  G06Q10/04 ,  G06Q50/04 ,  Y02P90/30

Abstract: A method and system for batch scheduling uniform parallel machines with different capacities based on an improved genetic algorithm are provided. The method is to solve the batch scheduling problem of uniform parallel machines with different capacities. Jobs are distributed to machines by an improved genetic algorithm, and a corresponding batching strategy and a batch scheduling strategy are proposed according to the natural of the problem to obtain a fitness value of a corresponding individual; then, the quality of the solution is improved by a local search strategy; and, a crossover operation is performed on a population based on the fitness of the solution, and the population is continuously updated by repetitive iteration to eventually obtain an optimal solution.