Outranking-based multi-objective PSO for scheduling unrelated parallel machines with a freight industry-oriented application

Rivera, Gilberto; Porras, Raúl; Sánchez-Solís, J. Patricia; Florencia, Rogelio; García, Vicente

doi:10.1016/j.engappai.2021.104556

Cited by 21 publications

(3 citation statements)

References 40 publications

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“…In recent studies, scheduling problems in parallel machine environments have been investigated across various industries, including semiconductor manufacturing [2,3], metalworking [4], textile manufacturing [5], automotive manufacturing [6,7], chemical processes [8], offshore oil and gas extraction [9], as well as manufacturing scheduling for contingent new requirements [10][11][12][13][14][15]. Additionally, scheduling challenges within service-related sectors have been studied, encompassing healthcare [7,16,17], audit [18], transport and cross-docking [19,20], hospital waste collection [21], emergency response for forest fire extinguishing [22], and drone scheduling problems [23], among others.…”

Section: Introductionmentioning

confidence: 99%

Developing New Bounds for the Performance Guarantee of the Jump Neighborhood for Scheduling Jobs on Uniformly Related Machines

Muñoz,

Latorre-Núñez,

Ramos-Maldonado

2023

Mathematics

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This study investigates the worst-case performance guarantee of locally optimal solutions to minimize the total weighted completion time on uniformly related parallel machines. The investigated neighborhood structure is Jump, also called insertion or move. This research focused on establishing the local optimality condition expressed as an inequality and mapping that maps a schedule into an inner product space so that the norm of the mapping is closely related to the total weighted completion time of the schedule. We determine two new upper bounds for the performance guarantee, which take the form of an expression based on parameters that describe the family of instances: the speed of the fastest machine, the speed of the slowest machine, and the number of machines. These new bounds outperform the parametric upper bound previously established in the existing literature and enable a better understanding of the performance of the solutions obtained for the Jump neighborhood in this scheduling problem, according to parameters that describe the family of instances.

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Section: Introductionmentioning

confidence: 99%

Developing New Bounds for the Performance Guarantee of the Jump Neighborhood for Scheduling Jobs on Uniformly Related Machines

Muñoz,

Latorre-Núñez,

Ramos-Maldonado

2023

Mathematics

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“…Parallel machine scheduling has been an interesting topic of research due to the breadth of its potential applications, [1][2][3][4][5][6] which include scheduled drilling mechanisms in printed circuit board manufacturing facilities, textile industry activities, dicing of semiconductor wafers used in computer manufacturing, and ship docking systems. 7 This popularity has grown significantly in recent years as a result of the development of parallel processor computing systems.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristics for optimizing unrelated parallel machines scheduling with unreliable resources to minimize makespan

Kaid

Al‐Ahmari

Al-Shayea

et al. 2022

Advances in Mechanical Engineering

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Parallel machines scheduling problems with continuous availability of machines are NP-hardness (non-deterministic polynomial-time hardness) and have become very popular for the last decade; there is still very limited literature on this problem. The purpose of this paper is to focus on the problem of scheduling n independent jobs to be processed on m unrelated identical parallel machines with availability constraints to minimize the maximum completion time of jobs (makespan). For this NP-hard problem, a mixed-integer linear programming (MILP) model is proposed to find an optimal solution for this problem. Two metaheuristics, tabu search (TS) and simulated annealing (SA) are proposed to solve large scale problem. Moreover, the performance of the solution obtained by the proposed metaheuristics is evaluated based on a lower bound, which decreases the time required to find the optimal solution. Extensive experiments are carried out to assess the performance of all proposed metaheuristics. The computational results highlight the ability of the proposed metaheuristics to obtain optimal solutions for most of the instances compared with the solutions of the proposed MILP model and lower bounds. Moreover, SA and TS can provide good efficiency for the problem in any jobs size and any machine size, but TS provides worse CPU time as the size of jobs become large.

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“…The unrelated parallel machine scheduling problem is a type of parallel machine scheduling problem. It is often seen in manufacturing industries, such as printed circuit board assembly [6], wafer fabrication [7], the textile industry [8], the transport industry [9], semiconductor wafer manufacturing [10], and supply chain scheduling problems [11]. Multiple machines can work simultaneously and independently in a parallel machine production environment.…”

Section: Introductionmentioning

confidence: 99%

Application of a Non-Dominated Sorting Genetic Algorithm to Solve a Bi-Objective Scheduling Problem Regarding Printed Circuit Boards

Chang

Zheng

2022

Mathematics

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An unrelated parallel machine scheduling problem motivated by the scheduling of a printed circuit board assembly (PCBA) under surface mount technology (SMT) is discussed in this paper. This problem involved machine eligibility restrictions, sequence-dependent setup times, precedence constraints, unequal job release times, and constraints of shared resources with the objectives of minimizing the makespan and the total job tardiness. Since this scheduling problem is NP-hard, a mathematical model was first built to describe the problem, and a heuristic approach using a non-dominated sorting genetic algorithm (NSGA-II) was then designed to solve this bi-objective problem. Multiple near-optimal solutions were provided using the Pareto front solution and crowding distance concepts. To demonstrate the efficiency and effectiveness of the proposed approach, this study first tested the proposed approach by solving test problems on a smaller scale. It was found that the proposed approach could obtain optimal solutions for small test problems. A real set of work orders and production data was provided by a famous hardware manufacturer in Taiwan. The solutions suggested by the proposed approach were provided using Gantt charts to visually assist production planners to make decisions. It was found that the proposed approach could not only successfully improve the planning time but also provide several feasible schedules with equivalent performance for production planners to choose from.

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Outranking-based multi-objective PSO for scheduling unrelated parallel machines with a freight industry-oriented application

Cited by 21 publications

References 40 publications

Developing New Bounds for the Performance Guarantee of the Jump Neighborhood for Scheduling Jobs on Uniformly Related Machines

Developing New Bounds for the Performance Guarantee of the Jump Neighborhood for Scheduling Jobs on Uniformly Related Machines

Metaheuristics for optimizing unrelated parallel machines scheduling with unreliable resources to minimize makespan

Application of a Non-Dominated Sorting Genetic Algorithm to Solve a Bi-Objective Scheduling Problem Regarding Printed Circuit Boards

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