A branch and bound algorithm for single machine scheduling with deteriorating values of jobs

Voutsinas, Theodore G.; Pappis, Costas P.

doi:10.1016/j.mcm.2009.12.024

Cited by 23 publications

(7 citation statements)

References 19 publications

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“…Although the optimal global solution can be obtained, it is only applicable to simple small-scale problems, with a large amount of calculation, high computational complexity, relatively slow solution speed, and strong dependence on the problem. [15][16][17] As most scheduling problems are NP-hard problems, it is impossible to find the exact solution of the scheduling problem by the polynomial algorithm. Therefore, most researches on flexible flow shop scheduling focus on the approximation methods, including heuristic algorithm and meta-heuristic algorithm.…”

Section: Comparison Of Workhop Scheduling Algorithmsmentioning

confidence: 99%

The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop

Wang

Jiang³

et al. 2020

Advances in Mechanical Engineering

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Roller grinding workshop is a typical multi-unit and multi-task manufacturing scenario, which is aimed to repair the surface damage of the rollers caused by the rolling process, so that the rollers can be reused. Due to the process complexity of roller grinding workshop and the large volume and weight of the roller, hoisting and transportation mode with multiple cranes is required. Consequently, the scheduling of the roller grinding workshop needs to consider both the task sequencing in time and the noninterference of the multi-crane trajectory in space. In this paper, the intelligent scheduling of roller grinding workshop is studied based on the characteristics of complex tasks and space-time coupling constraints. Firstly, the scheduling basis is established based on priority rules and process constraints. In order to solve the scheduling problem under the space-time coupling constraints, the position coordinate system is established, and then the algorithms of crane position tracking and cooperative motion without interference are developed. Further, considering the transportation time of crane and its out of sync time point with the processes, the intelligent decision and scheduling algorithm are developed based on the dynamic priority strategy defined to realize scheduling, including time decision, crane decision, and process decision. With the developed intelligent scheduling algorithm applied, the simulation of the roller grinding workshop is conducted under three combinations of priority strategy and noninterference strategy to verify algorithm performance. Under the guarantee of crane noninterference during the full production, the efficiency is improved by 22.1% compared with the existing processing mode of industry. Additionally, EPTR (effective process time rate) based on dynamic priority strategy and noninterference strategy B is up to 100% to avoid intervals between two processes in the scheduling. The dynamic priority developed in this paper reveals more efficiency than MOR principle, while with the strategy B the CUR (crane utilization rate) can be improved more than 20% under the condition of enough machines which facilitates to obtain shorter makespan than strategy A. The intelligent scheduling algorithm developed guarantees the effectiveness and rationality of scheduling with multi-unit and multi-task under the complex constraints. Finally, in order to realize the automatic and intelligent operation of the roller grinding workshop, the management software of the roller grinding workshop is developed by integrating the intelligent scheduling algorithm, which realizes the intelligent production, monitoring, and management of the roller grinding workshop during the full production cycle.

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Section: Comparison Of Workhop Scheduling Algorithmsmentioning

confidence: 99%

The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop

Wang

Jiang³

et al. 2020

Advances in Mechanical Engineering

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“…Computational results reveal that near-optimal solutions are achieved for a large number of problems. Janiak et al (2009) Finally, Voutsinas and Pappis (2010) add the B&B procedure to their earlier, near-optimal, job-sorting algorithm (2002) and determine optimal solutions. Results indicate a reduction in computation times, particularly as the number of jobs grow.…”

Section: Deteriorating Job Valuesmentioning

confidence: 99%

“…Beginning with two-step, core and allocation algorithm, heuristics have played an increasingly critical role in achieving near-optimal solutions to moderate and larger scale problems that can incorporate complexities and stochastic parameters. The heuristic procedures appear to be of several types: (1) extensions of RMRP/ MMRP applications, particularly the algorithm; (2) combining queuing analysis and computer simulation; (3) blending an IP formulation with LP relaxation, sub-problem generation and their solutions, and a feasibility reassurance procedure; (4) calculus-based procedures; (5) multi-stage algorithms typically including MP or total inventory-related cost formulations with Lagrangian relaxation, sub-problem decomposition, sub-problem solutions, and feasible reaggregation; and (6) other unique procedures (e.g., variant process planning (Veerakamolmal and Gupta 1998), sorting (Voutsinas and Pappis 2002), pairwise interchange (Stanfield, King, and Hodson 2006), testing multiple algorithms and selecting the best solution (e.g., Raut, Gupta and Swami 2008;Teunter, Tang, and Kaparis 2009), and combining sorting algorithms with a second-stage B&B solution procedure (Voutsinas and Pappis 2010)). …”

Section: Complexities Uncertainties and Stochasticitymentioning

confidence: 99%

A systematic literature review of remanufacturing scheduling

Morgan

Gagnon

2013

International Journal of Production Research

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This article systematically organises and reviews peer-reviewed journals up to July 2011 to access progress in the scheduling of remanufacturing operations. The simple (infinite capacity, no part commonality, and deterministic parameters), single product remanufacturing scheduling problem is solved using reverse material requirements planning. Material requirements planning and performance-based objectives of the 1990s were replaced by cost-based integer programming models that can achieve solutions to size-restricted problems. Product deterioration is identified as an additional complexity and methodologies are discussed that address this important issue. The synthesis of the literature reveals the importance of buffer inventories in addressing remanufacturing uncertainty, the advantages of 'simpler' disassembly release mechanisms and due date scheduling rules, and the improved performance of Kanban over 'push' scheduling and flexible Kanban over traditional Kanban. The most recent trend is the development and testing of several promising heuristic methodologies that can address larger and more complex, scheduling situations. Further study is still needed to address the formidable combinations of finite capacity, part commonality and stochastic parameters and, as Kim, Lee, and Xirouchakis (2007) note, the need to address backlogging, multiple periods, and the necessity to integrate disassembly process planning with disassembly scheduling.

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“…The scheduling literature describes the deterioration of jobs in two different ways. The first way is to define jobs whose processing times increase as their delays for processing increase (Voutsinas and Pappis, 2010). Most work in the area of deteriorating jobs focused on this description (Wang et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Maximizing total job value on a single machine with job selection

Eun

Sung

Kim

2017

Journal of the Operational Research Society

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This paper describes a single-machine scheduling problem of maximizing total job value with a machine availability constraint. The value of each job decreases over time in a stepwise fashion. Several solution properties of the problem are developed. Based on the properties, a branch-and-bound algorithm and a heuristic algorithm are derived. These algorithms are evaluated in the computational study, and the results show that the heuristic algorithm provides effective solutions within short computation times.

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A branch and bound algorithm for single machine scheduling with deteriorating values of jobs

Cited by 23 publications

References 19 publications

The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop

The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop

A systematic literature review of remanufacturing scheduling

Maximizing total job value on a single machine with job selection

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