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.

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.

Heuristics for the single machine weighted sum of completion times scheduling problem with periodic maintenance

2019 ◽  
Vol 75 (1) ◽  
pp. 291-320 ◽  
Author(s):  
Hanane Krim ◽  
Rachid Benmansour ◽  
David Duvivier ◽  
Daoud Aït-Kadi ◽  
Said Hanafi
Keyword(s):  
Single Machine ◽  
Weighted Sum ◽  
Scheduling Problem ◽  
Periodic Maintenance ◽  
Completion Times ◽  
Sum Of Completion Times

An Efficient Batch Scheduling Model for Hospital Sterilization Services Using Genetic Algorithm

2021 ◽  
pp. 928-946
Author(s):  
Shubin Xu ◽  
John Wang
Keyword(s):  
Genetic Algorithm ◽  
Medical Devices ◽  
Programming Model ◽  
Flow Time ◽  
Nonlinear Integer Programming ◽  
Batch Scheduling ◽  
Scheduling Problem ◽  
Work In Process ◽  
Completion Times ◽  
Sum Of Completion Times

A major challenge faced by hospitals is to provide efficient medical services. The problem studied in this article is motivated by the hospital sterilization services where the washing step generally constitutes a bottleneck in the sterilization services. Therefore, an efficient scheduling of the washing operations to reduce flow time and work-in-process inventories is of great concern to management. In the washing step, different sets of reusable medical devices may be washed together as long as the washer capacity is not exceeded. Thus, the washing step is modeled as a batch scheduling problem where washers have nonidentical capacities and reusable medical device sets have different sizes and different ready times. The objective is to minimize the sum of completion times for washing operations. The problem is first formulated as a nonlinear integer programming model. Given that this problem is NP-hard, a genetic algorithm is then proposed to heuristically solve the problem. Computational experiments show that the proposed algorithm is capable of consistently obtaining high-quality solutions in short computation times.

A TABU SEARCH ALGORITHM FOR A PIPE-PROCESSING FLOWSHOP SCHEDULING PROBLEM MINIMIZING TOTAL TARDINESS IN A SHIPYARD

2009 ◽  
Vol 26 (06) ◽  
pp. 817-829 ◽  
Author(s):  
XIAOFENG HU ◽  
JINGSONG BAO ◽  
YE JIN
Keyword(s):  
Tabu Search ◽  
Parallel Machines ◽  
Search Algorithm ◽  
Real Data ◽  
Total Tardiness ◽  
Tabu Search Algorithm ◽  
Scheduling Problem ◽  
Flowshop Scheduling ◽  
Pipe Processing ◽  
Flowshop Scheduling Problem

This paper focuses on scheduling problem of a pipe-processing flowshop in a shipyard. The flowshop composes of five stages, including cutting, bending, welding preprocessing, argon-welding and CO 2-welding, and each stage consists of identical parallel machines. Since thousands of pipes are mounted on the hull block before erection, the pipe-processing scheduling is a critical task for shipbuilding to meet the due date of the block erection. A tabu search algorithm is developed for the scheduling problem with the objective of minimizing total tardiness. Computational experiments are performed on the collected real data. Results show that the proposed algorithm is efficient for this problem.

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.

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