Two-agent single-machine scheduling with deteriorating jobs

Yin, Yunqiang; Cheng, T.C.E.; Wan, Long; Wu, Chin‐Chia; Liu, Jun

doi:10.1016/j.cie.2015.01.002

Cited by 38 publications

(17 citation statements)

References 42 publications

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“…For = 10 and = 0.2, the scheduling problems with = 0.2 required an average of 241,133 visited nodes to obtain an optimal solution, whereas scheduling problems with = 0.4 required 25,389 visited nodes, that is, 10% of the former case. Increasing shortens the due date in (23). A tight due date reduces the number of nodes that must be visited since many nodes violate the dominance properties of feasibility, rendering them fathomed.…”

Section: Analysis Of Experimental Resultsmentioning

confidence: 99%

“…Alidaee and Womer [22] carried out a review of various scheduling problems with linear aging effects noting their complexity and aging function form. Yin et al [23] suggested the single-machine scheduling problem with linear aging effect under two-agent consideration and provided the complexity and solvability information for various combinations of the two agents' objective functions.…”

Section: Introductionmentioning

confidence: 99%

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Sum-of-Processing-Times-Based Two-Agent Single-Machine Scheduling with Aging Effects and Tardiness

Kim

Choi

2015

Mathematical Problems in Engineering

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We consider a two-agent single-machine scheduling problem that minimizes the total weighted tardiness of one agent under the restriction that the second agent is prohibited from having tardy jobs. The actual processing times of all jobs are affected by a sum-of-processing-times-based aging effect. After showing the NP-hardness of the problem, we design a branch-and-bound (B&B) algorithm to find an optimal solution by developing dominance properties and a lower bound for the total weighted tardiness to increase search efficiency. Because B&B takes a long time to find an optimal solution, we propose a genetic algorithm as an efficient, near optimal solution approach. Four methods for generating initial populations are considered, and edge recombination crossover is adopted as a genetic operator. Through numerical experiments, we verify the outstanding performance of the proposed genetic algorithm.

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Section: Analysis Of Experimental Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sum-of-Processing-Times-Based Two-Agent Single-Machine Scheduling with Aging Effects and Tardiness

Kim

Choi

2015

Mathematical Problems in Engineering

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“…11 An agenda is a complete set of operations, with start and quit times for every activity, to be carried out with the aid of each system. 12 The time c program language period between the beginning of the primary process on the first system and the completing time of the remaining activity on the final machine is called as makespan. 13 The purpose of this problem is to decrease the makespan, which is described as crowning glory time of the ultimate process completed.…”

Section: Introductionmentioning

confidence: 99%

A vibrant crossbreed social spider optimization with genetic algorithm tactic for flexible job shop scheduling problem

Kavitha

Venkumar

2020

Measurement and Control

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Job shop scheduling is one of the major issues in which the scheduling process is associated with the real-time manufacturing industry. A flexible job shop scheduling problem is one of the most important issues among the hardest combinatorial advancement issues. Flexible job shop scheduling is extremely a nondeterministic polynomial combinatorial problem. In this paper, it is proposed that a mixture of improvement demonstrates to make makespan minimization in the flexible job shop scheduling problem issue. This paper includes the hybridization of social spider optimization and genetic algorithm that is effectively controlled by the calculation via optimization techniques. Most of the part in this method is given as the scavenging methodology of social insects, which use the vibrations spread over the bug-catching network to decide the position of the target. These hybridization approaches after arachnid upgrading process hereditary calculation chromosomes are chosen to produce new arrangements nearer to the minimum makespan time. The main objective of this paper is to minimize the makespan time of ''n'' jobs and ''m'' machines. The proposed algorithms have effectively investigated many benchmark problems and the computational results were compared with existing metaheuristic, including progressive calculations and algorithms for the swarm intelligence in the flexible job shop scheduling problem.

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“…For the total completion time minimization problem, they also gave some results. Yin et al [39,40,43] considered scheduling problems with time-dependent processing time (deteriorating jobs). Wang and Wang [28] considered single-machine scheduling with convex resource-dependent processing times.…”

Section: Introductionmentioning

confidence: 99%

Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine

Jin

et al. 2015

Neural Comput & Applic

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The focus of this paper is to analyze unrelated parallel-machine resource allocation scheduling problem with learning effect and deteriorating jobs. The goal is to find the optimal sequence of jobs and the optimal resource allocation separately for minimizing the cost function including the total load, the total completion time, the total absolute deviation of completion time and the total resource cost. We show that the problem is polynomial time solvable if the number of machines is a given constant.

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Two-agent single-machine scheduling with deteriorating jobs

Cited by 38 publications

References 42 publications

Sum-of-Processing-Times-Based Two-Agent Single-Machine Scheduling with Aging Effects and Tardiness

Sum-of-Processing-Times-Based Two-Agent Single-Machine Scheduling with Aging Effects and Tardiness

A vibrant crossbreed social spider optimization with genetic algorithm tactic for flexible job shop scheduling problem

Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine

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