scholarly journals Multi-objective multi-factory scheduling

2020 ◽  
Author(s):  
J. Behnamian ◽  
S.M.T. Fatemi Ghomi
Keyword(s):  
Heuristic Algorithm ◽  
Parallel Machines ◽  
Mixed Integer ◽  
Test Problems ◽  
Scheduling Problem ◽  
Production Network ◽  
Mixed Integer Linear Program ◽  
Multi Objective ◽  
Transportation Times ◽  
Factory Scheduling

This paper introducesa multi-factory scheduling problem with heterogeneous factories and parallel machines. This problem, as a major part of supply chain planning, includes the finding of suitable factory for each job and the scheduling of the assigned jobs at each factory, simultaneously. For the first time, this paper studies multi-objective scheduling in the production network in which each factory has its customers and demands can be satisfied by itself or other factories. In other words, this paper assumes that jobs can transfer from the overloaded machine in the origin factory to the factory which has fewer workloads by imposing some transportation times. For simultaneous minimization of the sum of the earliness and tardiness of jobs and total completion time, after modeling the scheduling problem as a mixed-integer linear program, the existing multi-objective techniques are analyzed and a new one is applied to our problem. Since this problem is NP-hard, a heuristic algorithm is also proposed to generate a set of Pareto optimal solutions. Also, the algorithms are proposed to improve and cover the Pareto front. Computational experiences of the heuristic algorithm and the output of the model implemented by CPLEX over a set of randomly generated test problems are reported.

scholarly journals Tabu search for a parallel-machine scheduling problem with periodic maintenance, job rejection and weighted sum of completion times

2021 ◽  
Author(s):  
Hanane Krim ◽  
Nicolas Zufferey ◽  
Jean-Yves Potvin ◽  
Rachid Benmansour ◽  
David Duvivier
Keyword(s):  
Tabu Search ◽  
Parallel Machines ◽  
Mixed Integer ◽  
Weighted Sum ◽  
Scheduling Problem ◽  
Maintenance Policy ◽  
Mixed Integer Linear Program ◽  
Job Rejection ◽  
Completion Times ◽  
Sum Of Completion Times

AbstractWe consider in this work a bicriteria scheduling problem on two different parallel machines with a periodic preventive maintenance policy. The two objectives considered involve minimization of job rejection costs and weighted sum of completion times. They are handled through a lexicographic approach, due to a natural hierarchy among the two objectives in the applications considered. The main contributions of this paper are first to present a new problem relevant to practice, second, to develop a mixed-integer-linear-program model for the problem, and third, to introduce two generalizable tabu-search metaheuristics relying on different neighborhood structures and solution spaces. Computational results for 120 instances (generated from a real case) are reported to empirically demonstrate the effectiveness of the proposed metaheuristics.

An Efficient Heuristic Algorithm for Solving Crane Scheduling Problem

2013 ◽  
Vol 442 ◽  
pp. 443-449
Author(s):  
Xie Xie ◽  
Yan Ping Li ◽  
Yong Yue Zheng ◽  
Xiao Li Li
Keyword(s):  
Heuristic Algorithm ◽  
Mixed Integer Linear Programming ◽  
Numerical Experiments ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Crane Scheduling ◽  
Technological Requirement ◽  
Iron And Steel ◽  
Analytical Properties ◽  
Upper Level

This paper focuses on a single crane scheduling problem which is motivated by cooled-rolling material warehouse in the iron and steel enterprise. As storage technological requirement, coils have been stored on the pre-specified position in two levels. If a demanded coil is in the upper level, it can be picked up directly. If a demanded coil in the lower level is blocked by un-demanded coils, the coil can not be transported until all the blocking coils are shuffled to another position. Our problem combines transportation and shuffling simultaneously for crane to pick up all demanded coils as early as possible to designated place (makespan). We first propose a mixed integer linear programming (MILP) model. Some analytical properties are further provided. Based on these properties, we propose a polynomial-time heuristic algorithm. Numerical experiments are carried out to confirm our proposed methods can provide high quality solutions.

scholarly journals Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Wenming Cheng ◽  
Peng Guo ◽  
Zeqiang Zhang ◽  
Ming Zeng ◽  
Jian Liang
Keyword(s):  
Variable Neighborhood Search ◽  
Parallel Machines ◽  
Programming Model ◽  
Search Algorithm ◽  
Optimal Schedule ◽  
Deteriorating Jobs ◽  
Mixed Integer ◽  
Computational Time ◽  
Neighborhood Search ◽  
Scheduling Problem

In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.

An integrated mathematical model of dynamic production and maintenance planning in pumped-storage hydroelectricity

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Farid Asgari ◽  
Fariborz Jolai ◽  
Farzad Movahedisobhani
Keyword(s):  
Mathematical Model ◽  
Exact Solution ◽  
Energy Production ◽  
Programming Model ◽  
Mixed Integer ◽  
Test Problems ◽  
Production Network ◽  
Content Type ◽  
The Difference ◽  
Pumped Storage

Purpose Pumped-storage hydroelectricity (PSH) is considered as an effective method to moderate the difference in demand and supply of electricity. This study aims to understanding of the high capacity of energy production, storage and permanent exploitation has been the prominent feature of pumped-storage hydroelectricity. Design/methodology/approach In this paper, the optimization of energy production and maintenance costs in one of the large Iranian PSH has been discussed. Hence, a mathematical model mixed integer nonlinear programming developed in this area. Minimizing the difference in supply and demand in the energy production network to multiple energies has been exploited to optimal attainment scheme. To evaluate the model, exact solution CPLEX and to solve the proposed programming model, the efficient metaheuristics are utilized by the tuned parameters achieved from the Taguchi approach. Further analysis of the parameters of the problem is conducted to verify the model behavior in various test problems. Findings The results of this paper have shown that the meta-heuristic algorithm has been done in a suitable time, despite the approximation of the optimal answer, and the consequences of research indicate that the model proposed in the studied power plant is applicable. Originality/value In pumped-storage hydroelectricity plants, one of the main challenges in energy production issues is the development of production, maintenance and repair scheduling concepts that improves plant efficiency. To evaluate the mathematical model presented, exact solution CPLEX and to solve the proposed bi-objective mixed-integer linear programming model, set of efficient metaheuristics are used. Therefore, according to the level of optimization performed in the case study, it has caused the improvement of planning by 7%–12% and effective optimization processes.

scholarly journals Balanced Scheduling of School Bus Trips using a Perfect Matching Heuristic

2018 ◽  
Vol 2672 (48) ◽  
pp. 1-11 ◽  
Author(s):  
Ali Shafahi ◽  
Sanaz Aliari ◽  
Ali Haghani
Keyword(s):  
Heuristic Algorithm ◽  
School Setting ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
School Bus ◽  
Heuristic Solution ◽  
Mip Model ◽  
Bus Scheduling ◽  
Minimum Number ◽  
The Cost

In the school bus scheduling problem, the main contributing factor to the cost is the number of buses needed for the operations. However, when subcontracting the pupils’ transportation, unbalanced tours can increase the costs significantly as the lengths of some tours can exceed the daily fixed driving goal and will result in over-hour charges. This paper proposes a mixed integer programming (MIP) model and a matching-based heuristic algorithm to solve the “balanced” school bus scheduling problem with fixed start times in a multi-school setting. The heuristic solution always has the minimum number of buses as it starts with a minimal number of tours and does not alter the number of tours during its balancing stage. The effectiveness of the heuristic is tested by comparing its solutions with results from solving the MIP using commercial solvers whenever solvers could find a good solution. To illustrate the performance of the MIP and the heuristic, 11 problems were examined with different numbers of trips which are all based on two real-world problems: a California case study with 54 trips and the Howard County Public School System with 994 trips. Our numerical results indicate the proposed heuristic algorithm can find reasonable solutions in a significantly shorter time. The balanced solutions of our algorithm can save up to 16% of school bus operation costs compared with the best solution found by solvers from optimizing the MIP model after 40 hours. The balancing stage of the heuristic decreases the standard deviation of the tour durations by up to 47%.

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