Bi-criteria ant colony optimization algorithm for minimizing makespan and energy consumption on parallel batch machines

Jia, Zhaohong; Zhang, Yulan; Leung, Joseph Y.-T.; Li, Kai

doi:10.1016/j.asoc.2017.01.044

Cited by 51 publications

(15 citation statements)

References 39 publications

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“…The problem P|r j , s j , p − batch|ND C max , EC is studied by Jia et al (2017) using a bi-criteria ant colony optimization (ACO) approach. Jia et al (2019) consider the same problem as in (Jia et al 2017), but the energy consumption of the machines in parallel can be different. Moreover, the ACO approach and the local search (LS) scheme are improved compared to the previous work.…”

Section: Discussion Of Related Workmentioning

confidence: 99%

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Bi-criteria parallel batch machine scheduling to minimize total weighted tardiness and electricity cost

2020

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A bi-criteria scheduling problem for parallel identical batch processing machines in semiconductor wafer fabrication facilities is studied. Only jobs belonging to the same family can be batched together. The performance measures are the total weighted tardiness and the electricity cost where a time-of-use (TOU) tariff is assumed. Unequal ready times of the jobs and non-identical job sizes are considered. A mixed integer linear program (MILP) is formulated. We analyze the special case where all jobs have the same size, all due dates are zero, and the jobs are available at time zero. Properties of Pareto-optimal schedules for this special case are stated. They lead to a more tractable MILP. We design three heuristics based on grouping genetic algorithms that are embedded into a non-dominated sorting genetic algorithm II framework. Three solution representations are studied that allow for choosing start times of the batches to take into account the energy consumption. We discuss a heuristic that improves a given near-to-optimal Pareto front. Computational experiments are conducted based on randomly generated problem instances. The -constraint method is used for both MILP formulations to determine the true Pareto front. For large-sized problem instances, we apply the genetic algorithms (GAs). Some of the GAs provide high-quality solutions.

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Section: Discussion Of Related Workmentioning

confidence: 99%

“…This includes memetic algorithms, GAs where each chromosome is improved by LS (Chiang et al 2010). LS procedures proposed for batch scheduling problems by Sobeyko and Mönch (2011) and Jia et al (2017) are adapted to problem (3) in Sect. 4.4.…”

Section: Basic Design Ideasmentioning

confidence: 99%

Bi-criteria parallel batch machine scheduling to minimize total weighted tardiness and electricity cost

2020

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“…The simultaneous minimization of the makespan and of the total electricity cost in identical parallel batch-processing machines was studied in [39]. The scheduling problem was solved using a Pareto-based ant colony algorithm.…”

Section: Identical Parallel Machinesmentioning

confidence: 99%

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

Renna

Materi

2021

Applied Sciences

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Climate change mitigation, the goal of reducing CO2 emissions, more stringent regulations and the increment in energy costs have pushed researchers to study energy efficiency and renewable energy sources. Manufacturing systems are large energy consumers and are thus responsible for huge greenhouse gas emissions; for these reasons, many studies have focused on this topic recently. This review aims to summarize the most important papers on energy efficiency and renewable energy sources in manufacturing systems published in the last fifteen years. The works are grouped together, considering the system typology, i.e., manufacturing system subclasses (single machine, flow shop, job shop, etc.) or the assembly line, the developed energy-saving policies and the implementation of the renewable energy sources in the studied contexts. A description of the main approaches used in the analyzed papers was discussed. The conclusion reports the main findings of the review and suggests future directions for the researchers in the integration of renewable energy in the manufacturing systems consumption models.

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“…Chen et al [ 34 ] proposed an entropy-based dynamic heterogeneous ant colony optimization to solve a large-scale traveling salesman problem. Jia et al [ 35 ] applied a local optimization strategy to optimize the ant colony algorithm, solving the problems of manufacturing time and energy consumption. Sun et al [ 36 ] used multiple ant colonies for the solution and determined strategies for information exchange among ant colonies according to the information entropy of each population to guarantee the balance of its convergence and diversity.…”

Section: Introductionmentioning

confidence: 99%

Path Planning of Pattern Transfer Based on Dual-Operator and a Dual-Population Ant Colony Algorithm for Digital Mask Projection Lithography

Wang

Han

et al. 2020

Entropy

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In the process of digital micromirror device (DMD) digital mask projection lithography, the lithography efficiency will be enhanced greatly by path planning of pattern transfer. This paper proposes a new dual operator and dual population ant colony (DODPACO) algorithm. Firstly, load operators and feedback operators are used to update the local and global pheromones in the white ant colony, and the feedback operator is used in the yellow ant colony. The concept of information entropy is used to regulate the number of yellow and white ant colonies adaptively. Secondly, take eight groups of large-scale data in TSPLIB as examples to compare with two classical ACO and six improved ACO algorithms; the results show that the DODPACO algorithm is superior in solving large-scale events in terms of solution quality and convergence speed. Thirdly, take PCB production as an example to verify the time saved after path planning; the DODPACO algorithm is used for path planning, which saves 34.3% of time compared with no path planning, and is about 1% shorter than the suboptimal algorithm. The DODPACO algorithm is applicable to the path planning of pattern transfer in DMD digital mask projection lithography and other digital mask lithography.

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Bi-criteria ant colony optimization algorithm for minimizing makespan and energy consumption on parallel batch machines

Cited by 51 publications

References 39 publications

Bi-criteria parallel batch machine scheduling to minimize total weighted tardiness and electricity cost

Bi-criteria parallel batch machine scheduling to minimize total weighted tardiness and electricity cost

A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

Path Planning of Pattern Transfer Based on Dual-Operator and a Dual-Population Ant Colony Algorithm for Digital Mask Projection Lithography

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