Unrelated parallel machine scheduling with setup consideration and a total weighted completion time objective

Weng, Meng-Hsiung; Lu, Ja-Yu; Ren, Haiying

doi:10.1016/s0925-5273(00)00066-9

Cited by 139 publications

(64 citation statements)

References 15 publications

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“…(Kimms, 1999) developed genetic algorithms to solve the multi-machine lot-sizing and scheduling problem, considering some scarce resources, but the main assumption is that at most one setup can occur per period. (Weng et al, 2001) proposed several heuristics to solve the problem of scheduling independent jobs on a set of unrelated parallel machines with sequence dependent setup times. (Kim et al, 2002) used simulated annealing to solve a similar problem but in which items of one job can be split among several machines.…”

Section: Considered Problemmentioning

confidence: 99%

A Generic Decision Support Tool for Lot-Sizing and Scheduling Problems with Setup and Due Dates

Silva

Klement

Gibaru

2017

Lecture Notes in Management and Industrial Engineering

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. Abstract: Decision support tools are essential to help in the management of industrial systems at different levels: strategic, to design the system; tactical to plan activities or assign resources; operational to schedule activities. In this paper, we present a generic and modular decision support tool to solve different planning, assignment, scheduling or lot-sizing problems. To the best of our knowledge, such generic tool does not exist. The methodology is illustrated by solving a real world lot-sizing and scheduling problem from a plastic injection company.

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Section: Considered Problemmentioning

confidence: 99%

A Generic Decision Support Tool for Lot-Sizing and Scheduling Problems with Setup and Due Dates

Silva

Klement

Gibaru

2017

Lecture Notes in Management and Industrial Engineering

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“…As noted by Wex et al [11], such a problem is similar to the multiple Traveling Salesman Problem with salesman-specific travel times or the parallel-machine scheduling problem with unrelated machines non-batch sequence-dependent setup times. Apart from the work of Wex et al, according to Weng et al [12] only one research paper on the above problem has been published, and it does not provide specific definition of the operational constraints. A major difference between all of the above work and this research is the hard constraint we impose on operation time.…”

Section: A Problem Descriptionmentioning

confidence: 99%

Particle Swarm Optimization/Greedy-Search Algorithm for Helicopter Mission Assignment in Disaster Relief

Andreeva-Mori

Kobayashi

Shindo

2015

Journal of Aerospace Information Systems

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In the immediate aftermath of a large-scale disaster, optimal helicopter rescue mission assignment is critical to saving many lives. The current practice in the field is mostly humancentered, however. Japan Aerospace Exploration Agency has been developing a decisionsupport system for aircraft operation in order to promptly plan and execute rescue missions.The current research focuses on evacuation missions in particular and investigates the potential of particle swarm optimization (PSO) with integrated greedy search in aircraft resource management. We propose a robust particle model which can reflect various

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“…With regard to the problem formulation of RUASP, any formulation of the scheduling problem R/ST SD /∑w j C j may be used and modified so that the property that different rescue units need different travel times between the locations of the incidents is accounted for. However, according to the review paper by Allahverdi et al (2008), there is only one paper on this scheduling problem (Weng et al, 2001). While this paper suggests a recursive objective function, it specifies the constraints at high level only.…”

Section: Relationship To Routing and Scheduling Problemsmentioning

confidence: 99%

A Fuzzy Decision Support Model for Natural Disaster Response under Informational Uncertainty

Wex

Schryen

Neumann

2012

International Journal of Information Systems for Crisis Response and Management

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Coordination deficiencies have been identified after the March 2011 earthquakes in Japan in terms of scheduling and allocation of resources, with time pressure, resource shortages, and especially informational uncertainty being main challenges. We address this issue of operational emergency response in natural disaster management (NDM) by suggesting a decision support model and a Monte Carlo heuristic which account for these challenges by drawing on fuzzy set theory and fuzzy optimization.Deriving requirements for addressing NDM situations from both practice and literature, we propose a decision model that accounts for the following phenomena: a) incidents and rescue units are spatially distributed, b) rescue units possess specific capabilities, c) processing is non-preemptive, and d) informational uncertainty occurs due to vague and linguistic specifications of data. We computationally evaluate our heuristic and benchmark the results with current best practice solutions. Our results indicate that applying the new heuristic can substantially reduce overall harm.

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Unrelated parallel machine scheduling with setup consideration and a total weighted completion time objective

Cited by 139 publications

References 15 publications

A Generic Decision Support Tool for Lot-Sizing and Scheduling Problems with Setup and Due Dates

A Generic Decision Support Tool for Lot-Sizing and Scheduling Problems with Setup and Due Dates

Particle Swarm Optimization/Greedy-Search Algorithm for Helicopter Mission Assignment in Disaster Relief

A Fuzzy Decision Support Model for Natural Disaster Response under Informational Uncertainty

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