Bi-objective optimization for single-machine batch scheduling considering energy cost

Cheng, Jiubing; Xia, Weili; Ding, Jiachen; Ling, Xiang

doi:10.1109/codit.2014.6996899

Cited by 8 publications

(16 citation statements)

References 27 publications

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“…We start by discussing related work for single and parallel batch processing machines with EC-related objectives. The problem 1|p − batch, p j ≡ p|ND C max , EC is discussed by Cheng et al (2014). All jobs have the same processing time, i.e., there is only a single job family.…”

Section: Discussion Of Related Workmentioning

confidence: 99%

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%

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

2020

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“…On the contrary, a batch is closed without any job and its corresponding processing time equals to 0, i.e., P b = 0. Now the considered problem can be formulated as the following bi-objective MILP model P [3].…”

Section: Decision Variablesmentioning

confidence: 99%

“…As mentioned above, the number of batch k equals to the number of jobs n in model P. we can observe that the solution search space of the model is very large, since it is already time consuming even k is set as its lower bound n/C in [3]. This subsection is devoted to reducing the search space via problem property analysis.…”

Section: Complexity and Properties Of T Ou 1|b|c Max Ecmentioning

confidence: 99%

“…To the best of our knowledge, our preliminary work [3] is the first study on batch scheduling under TOU policy, in which the makespan and the total electricity costs are simultaneously considered. In [3], a nonlinear bi-objective model was formulated. The ε-constraint method was used to solve the bi-objective model.…”

Section: Introductionmentioning

confidence: 99%

“…The corresponding single-objective models considered in the ε-constraint method were linearized via theoretical properties, and 75 instances with up to 40 jobs were tested. However, the complexity of the considered problem was not demonstrated and the proofs of the properties were not given in [3].…”

Section: Introductionmentioning

confidence: 99%

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Bi-objective optimization of single-machine batch scheduling under time-of-use electricity prices

et al. 2016

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Time-of-use (TOU) electricity pricing has been a common practice to enhance the peak load regulation capability of power grid. Meanwhile, it provides a good opportunity for industries to reduce energy costs, especially for energy-intensive ones, where batch scheduling is often involved. Majority of batch scheduling problems have been proved to be NP-hard, even for most single-machine environments. Optimizing batch scheduling under TOU policy in these industries will be of great significance. Singlemachine batch scheduling is an important basis for more complicated shop scheduling problems. This paper investigates a bi-objective single-machine batch scheduling problem under TOU policy: the first objective is to minimize the makespan and the second is to minimize the total electricity costs. The considered problem is first formulated as a bi-objective mix-integer linear programming (MILP) model and is demonstrated to be NP-hard. Subsequently, the MILP is simplified by analyzing properties and search space for a Pareto optimal solution is greatly reduced. Then, an exact ε-constraint method is adapted to obtain its Pareto front, which is accelerated due to these properties. Finally, a preferable solution is recommended for decision makers via a fuzzy-logic-based approach. Computational results on randomly generated instances show the effectiveness of the proposed approach.

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Large-scale energy-conscious bi-objective single-machine batch scheduling under time-of-use electricity tariffs via effective iterative heuristics

Cheng

2019

Ann Oper Res

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Bi-objective optimization for single-machine batch scheduling considering energy cost

Cited by 8 publications

References 27 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

Bi-objective optimization of single-machine batch scheduling under time-of-use electricity prices

Large-scale energy-conscious bi-objective single-machine batch scheduling under time-of-use electricity tariffs via effective iterative heuristics

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