scholarly journals A mathematical model for teamwork scheduling problem in available time-windows

2020 ◽  
Vol 3 (SI1) ◽  
pp. First
Author(s):  
Sơn Hồng Trang ◽  
Lăng Văn Trần ◽  
Nguyên Tường Huỳnh
Keyword(s):  
Mathematical Model ◽  
Heuristic Algorithms ◽  
Time Windows ◽  
Computing Time ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Feasible Schedule ◽  
Maximum Completion Time ◽  
Simple Heuristics ◽  
Assignment Approach

This paper deals with teamwork scheduling problem in available time windows. This problem has been posed by combining the three constraints are the jobs can split into some sub-jobs which should not be less than a threshold called splitmin, the jobs are only assigned into available time windows and the jobs can be assigned into many people in the organization. Since then the four properties of this problem considered are everyone handles any jobs; a job can be handled by some person at the same time; jobs can be broken down into some sub-jobs; the size of the job/sub-job should not be less than splitmin. The goal aims to determine a feasible schedule that minimizes makespan. And a numerical example is presented to demonstrate the essential constraint with given input data to well define this scheduling problem. Besides the authors proposed a mathematical model to determine the optimal solution by using solvers to solve it and some simple heuristics with computing time less than one second to find the good solutions such as Assignment approach, SPT/LPT rules. All experiments were evaluated on two criteria are the maximum completion time for all jobs and runtime in seconds to determine the solution. These experiments were conducted by the comparison of the lower bound, the exact method based on using CPLEX solver to solve the MILP model, and proposed heuristics. The experimental results show it is very time consuming to determine the optimal solution by CPLEX solver, while the solution found by heuristic algorithms is only good enough.

scholarly journals Minimizing makespan of Personal Scheduling problem in available time-windows with split-min and setup-time constraints

2018 ◽  
Vol 34 (2) ◽  
pp. 97-111
Author(s):  
SON HONG TRANG ◽  
NGUYEN TUONG HUYNH ◽  
LANG VAN TRAN
Keyword(s):  
Tabu Search ◽  
Search Algorithm ◽  
Time Windows ◽  
Optimal Solution ◽  
Setup Time ◽  
Exact Method ◽  
Time Constraints ◽  
Tabu Search Algorithm ◽  
Scheduling Problem ◽  
Maximum Completion Time

This paper deals with personal scheduling problem in available time-windows with split-min and setup-time constraints. The jobs are splitable into sub-jobs and a common lower bound on the size of each sub-job is imposed. The objective function aims to find a feasible schedule that minimizes the maximum completion time of all jobs. The proposed scheduling problem was proved to be strongly NP-hard by a reduction to 3-SAT problem in the preliminary results. We propose in this paper an exact method based on MILP model to find optimal solution, some heuristics to find feasible solution and a meta-heuristic based on tabu search algorithm to find good solution. The computational results show the performance of proposed exact method, some heuristics and tabu search algorithm.

A Petri Net and Genetic Algorithm Based Method for Flexible Manufacturing Cells Modeling and Scheduling

2009 ◽  
Vol 407-408 ◽  
pp. 268-272 ◽  
Author(s):  
Li Hong Qiao ◽  
Yi Xin Zhu ◽  
Jian Jun Yang ◽  
Yang Li
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Petri Net ◽  
Flexible Manufacturing ◽  
Simulated Annealing Algorithm ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Manufacturing Cells ◽  
Flexible Manufacturing Cells ◽  
Annealing Algorithm

The production organized in flexible manufacturing cells (FMC) can be a complicated issue when they are constrained by machines, robots, equipment and some other resources. Since machines and robots are the main bottleneck to the efficiency of FMC, this paper focused on the modeling and scheduling problem constrained by machines and robots. A common model representation, colored timed Petri net (CTPN) was utilized to build a FMC model constrained by robots and machines, which was then transformed to the simulation model. The scheduling problem was studied to establish a mathematical model of the FMC constrained by machines and robots. According to the model, a genetic algorithm was proposed to search an optimal solution by using an indirect coding of scheme. The effectiveness of the proposed algorithm was validated via an instance and the comparison with the result from the solution of simulated annealing algorithm.

scholarly journals Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammed Al-Salem ◽  
Leonardo Bedoya-Valencia ◽  
Ghaith Rabadi
Keyword(s):  
Job Shop ◽  
Heuristic Algorithms ◽  
Job Shop Scheduling ◽  
Optimal Solution ◽  
Approximate Solutions ◽  
Exact Algorithms ◽  
Just In Time ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling

The problem addressed in this paper is the two-machine job shop scheduling problem when the objective is to minimize the total earliness and tardiness from a common due date (CDD) for a set of jobs when their weights equal 1 (unweighted problem). This objective became very significant after the introduction of the Just in Time manufacturing approach. A procedure to determine whether the CDD is restricted or unrestricted is developed and a semirestricted CDD is defined. Algorithms are introduced to find the optimal solution when the CDD is unrestricted and semirestricted. When the CDD is restricted, which is a much harder problem, a heuristic algorithm is proposed to find approximate solutions. Through computational experiments, the heuristic algorithms’ performance is evaluated with problems up to 500 jobs.

scholarly journals Fairness Time-Slot Allocation and Scheduling with QoS Guarantees in Multihop WiMAX Mesh Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Chien-Yu Wu ◽  
Hann-Jang Ho ◽  
Sing-Ling Lee ◽  
Liang Lung Chen
Keyword(s):  
Large Scale ◽  
Heuristic Algorithms ◽  
Mesh Networks ◽  
Time Slot ◽  
Optimal Solution ◽  
Small Scale ◽  
Scheduling Problem ◽  
Slot Allocation ◽  
Long Distance ◽  
Time Slot Allocation

The WiMAX technology has been defined to provide high throughput over long distance communications and support the quality of service (QoS) control applied on different applications. This paper studies the fairness time-slot allocation and scheduling problem for enhancing throughput and guaranteeing QoS in multihop WiMAX mesh networks. For allocating time slots to multiple subscribe stations (SSs), fairness is a key concern. The notion of max-min fairness is applied as our metric to define the QoS-based max-min fair scheduling problem for maximizing the minimum satisfaction ratio of each SS. We formulate an integer linear programming (ILP) model to provide an optimal solution on small-scale networks. For large-scale networks, several heuristic algorithms are proposed for better running time and scalability. The performance of heuristic algorithms is compared with previous methods in the literatures. Experimental results show that the proposed algorithms are better in terms of QoS satisfaction ratio and throughput.

Optimized Vehicle Scheduling Algorithm of Distribution Center

2013 ◽  
Vol 340 ◽  
pp. 581-586
Author(s):  
Zhu Wang
Keyword(s):  
Mathematical Model ◽  
Scheduling Algorithm ◽  
Time Windows ◽  
Distribution Center ◽  
Vehicle Scheduling ◽  
Scheduling Problem ◽  
Research Results ◽  
Logistics Distribution ◽  
The Mathematical Model

This thesis goes deep into the vehicle scheduling problem (VSP), which is the key problem for the distribution center.This paper analyzes and optimizes the mathematical model of vehicle scheduling problem. The problem of dynamic vehicle scheduling with time windows is described in great details in the thesis, which also gives an arithmetic solution aiming at the scheduling problem.Finally, based on the research results and under the background of logistics distribution enterprises, the vehicle scheduling algorithm is exposed to experiment.

The R-PSO algorithm solving multi-skill resource-constrained project scheduling problem

2021 ◽  
pp. 71-82
Author(s):  
Dang Quoc Huu
Keyword(s):  
Project Scheduling ◽  
Optimal Solution ◽  
Simulated Data ◽  
Pso Algorithm ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Feasible Schedule ◽  
Approximate Methods ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem

The Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP) is a combinational optimization problem with many applications in science and practical areas. This problem aims to find out the feasible schedule for the completion of projects and workflows that is minimal duration or cost (or both of them - multi objectives). The researches show that MS-RCPSP is classified into NP-Hard classification, which could not get the optimal solution in polynomial time. Therefore, we usually use approximate methods to carry out the feasible schedule. There are many publication results for that problem based on evolutionary methods such as GA, Greedy, Ant, etc. However, the evolutionary algorithms usually have a limitation that is fallen into local extremes after a number of generations. This paper will study a new method to solve the MS-RCPSP problem based on the Particle Swarm Optimization (PSO) algorithm that is called R-PSO. The new improvement of R-PSO is re-assigning the resource to execute solution tasks. To evaluate the new algorithm's effectiveness, the paper conducts experiments on iMOPSE datasets. Experimental results on simulated data show that the proposed algorithm finds a better schedule than related works.

The Research on the Optimization of Transportation Routing for Fresh Food by Improved Genetic Algorithm

2012 ◽  
Vol 178-181 ◽  
pp. 1790-1796 ◽  
Author(s):  
Ying Wu ◽  
Zi Bo Meng ◽  
Min Peng
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Customer Satisfaction ◽  
Time Window ◽  
Time Windows ◽  
Optimal Solution ◽  
Improved Genetic Algorithm ◽  
Transport Services ◽  
Fresh Food ◽  
Transportation Routing

In this paper, we research the problem of transportation routing for fresh food. We analyzed the limit of soft and hard time windows in transportation and formed the time window with fuzzy appointment based on customer satisfaction. The optimization of transportation routes mathematical model was structured. The improved genetic algorithm has been applied to matlab progam. This progam has found the optimal solution in the model. We used a case to prove the feasibility of the model and the algorithm. It has twelve customers and one DC need to transport services. The mathematical model is to simulate the transport of fresh food within realistic.The transportation routing is designed to improve customer satisfaction and reduce transportation costs.

scholarly journals Optimal solving of the pump scheduling problem by using a Harmony Search optimization algorithm

2017 ◽  
Vol 19 (6) ◽  
pp. 879-889 ◽  
Author(s):  
F. De Paola ◽  
N. Fontana ◽  
M. Giugni ◽  
G. Marini ◽  
F. Pugliese
Keyword(s):  
Optimization Algorithm ◽  
Water Distribution ◽  
Heuristic Algorithms ◽  
Water Pressure ◽  
Harmony Search ◽  
Optimal Solution ◽  
Distribution Networks ◽  
Scheduling Problem ◽  
Pump Operation ◽  
Pump Scheduling

Abstract Pumps are installed in water distribution networks (WDNs) to ensure adequate service levels in the case of poor water pressure (e.g. because of low elevation of reservoirs or high head losses within the WDN). In such cases optimal pump scheduling is often required for the opportunity of significant energy saving. Optimizing the pump operation also allows a reduction in damage and maintenance times. Among the approaches available in the literature to solve the problem, meta-heuristic algorithms ensure reduced computational times, although they are not able to guarantee the optimal solution can be found. In this paper, a modified Harmony Search Multi-Objective optimization algorithm is developed to solve the pump scheduling problem in WDNs. The hydraulic solver EPANET 2.0 is coupled with the algorithm to assess the feasibility of the achieved solutions. Hydraulic constraints are introduced and penalties are set in case of violation of the set constraints to reduce the space of feasible solutions. Results show the high performances of the proposed approach for pumping optimization, guaranteeing optimal (or near optimal) solutions with short computational times.

scholarly journals The operational flight and multi-crew scheduling problem

2005 ◽  
Vol 15 (1) ◽  
pp. 25-48 ◽  
Author(s):  
Mirela Stojkovic ◽  
François Soumis
Keyword(s):  
Network Flow ◽  
Time Windows ◽  
Optimal Solution ◽  
Crew Scheduling ◽  
Scheduling Problem ◽  
Sequential Approach ◽  
Solution Approach ◽  
Departure Time ◽  
New Type ◽  
Crew Scheduling Problem

This paper introduces a new kind of operational multi-crew scheduling problem which consists in simultaneously modifying, as necessary, the existing flight departure times and planned individual work days (duties) for the set of crew members, while respecting predefined aircraft itineraries. The splitting of a planned crew is allowed during a day of operations, where it is more important to cover a flight than to keep planned crew members together. The objective is to cover a maximum number of flights from a day of operations while minimizing changes in both the flight schedule and the next-day planned duties for the considered crew members. A new type of the same flight departure time constraints is introduced. They ensure that a flight which belongs to several personalized duties, where the number of duties is equal to the number of crew members assigned to the flight, will have the same departure time in each of these duties. Two variants of the problem are considered. The first variant allows covering of flights by less than the planned number of crew members, while the second one requires covering of flights by a complete crew. The problem is mathematically formulated as an integer nonlinear multi-commodity network flow model with time windows and supplementary constraints. The optimal solution approach is based on Dantzig-Wolfe decomposition/column generation embedded into a branch-and-bound scheme. The resulting computational times on commercial-size problems are very good. Our new simultaneous approach produces solutions whose quality is far better than that of the traditional sequential approach where the flight schedule has been changed first and then input as a fixed data to the crew scheduling problem.

scholarly journals Personnel Scheduling Problem under Hierarchical Management Based on Intelligent Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Li Huang ◽  
Chunming Ye ◽  
Jie Gao ◽  
Po-Chou Shih ◽  
Franley Mngumi ◽  
...  
Keyword(s):  
Heuristic Algorithms ◽  
Optimal Solution ◽  
Grey Wolf Optimizer ◽  
Scheduling Problem ◽  
Nurse Scheduling ◽  
Intelligent Algorithm ◽  
Charge Nurses ◽  
Hierarchical Management ◽  
Two Hybrid ◽  
Better Than

This paper studies a special scheduling problem under hierarchical management in nurse staff. This is a more complex rostering problem than traditional nurse scheduling. The first is that the rostering requirements of charge nurses and general nurses are different under hierarchical management. The second is that nurses are preferable for relative fair rather than absolute fair under hierarchical management. The model aims at allocating the required workload to meet the operational requirements, weekend rostering preferences, and relative fairness preferences. Two hybrid heuristic algorithms based on multiobjective grey wolf optimizer (MOGWO) and three corresponding single heuristic algorithms are employed to solve this problem. The experimental results based on real cases from the Third People’s Hospital, Panzhihua, China, show that MOGWO does not as good as it does on other engineering optimization. However, the hybrid algorithms based on MOGWO are better than corresponding single algorithms on generational distance (GD) and spacing (SP) of Pareto solutions. Furthermore, for relative fair rostering objective, NSGAII-MOGWO has more power to find the optimal solution in the dimension of relative fairness.

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