Minimizing Total Tardiness in Parallel-Machine Scheduling with Release Dates

2012 ◽  
Vol 3 (1) ◽  
pp. 21-46 ◽  
Author(s):  
Farouk Yalaoui
Keyword(s):  
Ant Colony Algorithm ◽  
Parallel Machines ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Total Tardiness ◽  
Release Dates ◽  
Identical Parallel Machines ◽  
Priority Rules ◽  
Release Date ◽  
Exact Resolution

The considered problem is the scheduling of a set of jobs on identical parallel machines in order to minimize the total tardiness without any preemption or splitting. Each job has its own processing time, release date and due date. All the machines are considered identical (with same speed) and available during all the scheduling period. This problem is NP-hard. An exact resolution, an Ant Colony Algorithm (ACO), a Tabu Search (TS) method, a set of Heuristics based on priority rules and an adapted Biskup Hermann Gupta (BHG) method are proposed to solve the problem. The obtained results are discussed and analyzed.

An Optimal Preemptive Algorithm for the Single-Server Parallel-Machine Scheduling with Loading and Unloading Times

2014 ◽  
Vol 31 (05) ◽  
pp. 1450039 ◽  
Author(s):  
Yiwei Jiang ◽  
Huijuan Wang ◽  
Ping Zhou
Keyword(s):  
Parallel Machines ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Solution Algorithm ◽  
Single Server ◽  
Preemptive Scheduling ◽  
Scheduling Problem ◽  
Identical Parallel Machines ◽  
Loading And Unloading

We study a preemptive scheduling problem on two identical parallel machines that share a common server. Each job has to be loaded by the server before being processed on one of the machines and unloaded by the server after its processing. The loading and unloading times are both equal to one time unit. The goal is to minimize the makespan. We propose a O(n log n) solution algorithm for the preemptive variant of the problem.

scholarly journals An Ant Optimization Model for Unrelated Parallel Machine Scheduling with Energy Consumption and Total Tardiness

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Peng Liang ◽  
Hai-dong Yang ◽  
Guo-sheng Liu ◽  
Jian-hua Guo
Keyword(s):  
Energy Consumption ◽  
Parallel Machines ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Taguchi Methods ◽  
Total Tardiness ◽  
Unrelated Parallel Machine ◽  
Heuristic Rule ◽  
Unrelated Parallel Machine Scheduling

This research considers an unrelated parallel machine scheduling problem with energy consumption and total tardiness. This problem is compounded by two challenges: differences of unrelated parallel machines energy consumption and interaction between job assignments and machine state operations. To begin with, we establish a mathematical model for this problem. Then an ant optimization algorithm based on ATC heuristic rule (ATC-ACO) is presented. Furthermore, optimal parameters of proposed algorithm are defined via Taguchi methods for generating test data. Finally, comparative experiments indicate the proposed ATC-ACO algorithm has better performance on minimizing energy consumption as well as total tardiness and the modified ATC heuristic rule is more effectively on reducing energy consumption.

BicriteriaHeuristic for Unrelated Parallel Machine Scheduling Problem

2014 ◽  
Vol 1016 ◽  
pp. 824-828
Author(s):  
Yang Kuei Lin ◽  
Hao Chen Lin
Keyword(s):  
Parallel Machines ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Release Dates ◽  
Scheduling Problem ◽  
Unrelated Parallel Machines ◽  
Weighted Tardiness ◽  
Unrelated Parallel Machine Scheduling ◽  
Parallel Machine Scheduling Problem

In this research, a bi-criteria heuristic is proposed to find non-dominated solutions for scheduling unrelated parallel machines with release dates that minimizes makespan andtotal weighted tardiness.

No-idle parallel-machine scheduling of unit-time jobs with a small number of distinct release dates and deadlines

2021 ◽  
Vol 132 ◽  
pp. 105315
Author(s):  
Nadia Brauner ◽  
Mikhail Y. Kovalyov ◽  
Alain Quilliot ◽  
Hélène Toussaint
Keyword(s):  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Release Dates

scholarly journals Decomposition approaches for parallel machine scheduling of step-deteriorating jobs to minimize total tardiness and energy consumption

2021 ◽  
Author(s):  
Xiao Wu ◽  
Peng Guo ◽  
Yi Wang ◽  
Yakun Wang
Keyword(s):  
Energy Consumption ◽  
Tabu Search ◽  
Processing Time ◽  
Deteriorating Jobs ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Total Tardiness ◽  
Master Problem ◽  
Starting Time ◽  
Extra Energy

AbstractIn this paper, an identical parallel machine scheduling problem with step-deteriorating jobs is considered to minimize the weighted sum of tardiness cost and extra energy consumption cost. In particular, the actual processing time of a job is assumed to be a step function of its starting time and its deteriorating threshold. When the starting time of a job is later than its deteriorating threshold, the job faces two choices: (1) maintaining its status in holding equipment and being processed with a base processing time and (2) consuming an extra penalty time to finish its processing. The two work patterns need different amounts of energy consumption. To implement energy-efficient scheduling, the selection of the pre-processing patterns must be carefully considered. In this paper, a mixed integer linear programming (MILP) model is proposed to minimize the total tardiness cost and the extra energy cost. Decomposition approaches based on logic-based Benders decomposition (LBBD) are developed by reformulating the studied problem into a master problem and some independent sub-problems. The master problem is relaxed by only making assignment decisions. The sub-problems are to find optimal schedules in the job-to-machine assignments given by the master problem. Moreover, MILP and heuristic based on Tabu search are used to solve the sub-problems. To evaluate the performance of our methods, three groups of test instances were generated inspired by both real-world applications and benchmarks from the literature. The computational results demonstrate that the proposed decomposition approaches can compute competitive schedules for medium- and large-size problems in terms of solution quality. In particular, the LBBD with Tabu search performs the best among the suggested four methods.

scholarly journals Scheduling on a Single Machine and Parallel Machines with Batch Deliveries and Potential Disruption

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hua Gong ◽  
Yuyan Zhang ◽  
Puyu Yuan
Keyword(s):  
Polynomial Time ◽  
Single Machine ◽  
Manufacturing Industry ◽  
Parallel Machines ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Approximation Schemes ◽  
Scheduling Problems ◽  
Delivery Scheduling ◽  
Production Part

In this paper, we study several coordinated production-delivery scheduling problems with potential disruption motivated by a supply chain in the manufacturing industry. Both single-machine environment and identical parallel-machine environment are considered in the production part. The jobs finished on the machines are delivered to the same customer in batches. Each delivery batch has a capacity and incurs a delivery cost. There is a situation that a possible disruption in the production part may occur at some particular time and will last for a period of time with a probability. We consider both resumable case and nonresumable case where a job does not need (needs) to restart if it is disrupted for a resumable (nonresumable) case. The objective is to find a coordinated schedule of production and delivery that minimizes the expected total flow times plus the delivery costs. We first present some properties and analyze the NP-hard complexity for four various problems. For the corresponding single-machine and parallel-machine scheduling problems, pseudo-polynomial-time algorithms and fully polynomial-time approximation schemes (FPTASs) are presented in this paper, respectively.

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