A note on task assignment of several problems

Alidaee, Bahram; Gao, Hongman; Wang, Haibo

doi:10.1016/j.cie.2010.07.010

Cited by 15 publications

(17 citation statements)

References 16 publications

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“…In a number of surveillance and delivery applications, drones have to perform a tour over some set of locations which starts and ends at a depot. The resulting planning problems can be modeled as generalized versions of one of the basic routing problems, such as the TSP , the multiple TSP , or the VRP .…”

Section: Planning Drone Operationsmentioning

confidence: 99%

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

et al. 2018

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Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult‐to‐access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

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Section: Planning Drone Operationsmentioning

confidence: 99%

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

et al. 2018

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“…The model by [21], however, has exponential number of variables. An improved compact formulation of such assignment problems and several other assignment problems recently was given by [23]. In the next section, we present a computational experiment of our FDA/UAV model and computationally compare with the formulation of [19].…”

Section: Subject Tomentioning

confidence: 99%

On the Flexible Demand Assignment Problems: Case of Unmanned Aerial Vehicles

Alidaee

Wang

Landram

2011

IEEE Trans. Automat. Sci. Eng.

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Multiresource generalized assignment problem (MRGAP) has enormous applications in solving real problems of industries. In recent years, several generalizations of MRGAP have been proposed to tackle very difficult problems. An important generalization is called flexible demand assignment (FDA) problem. In this paper, a generalization of FDA is proposed that has many applications. Two features of our formulation are inclusion of: 1) acceptance of orders from a large set of available orders and 2) consideration of setup time between operations of two consecutive of tasks. We show an interesting application of generalized FDA is unmanned aerial vehicle (UAV) assignment problem. For the UAV assignment problem, we show our formulation considerably reduces the size of the problem compared to some recent results. To test effectiveness of the proposed model, computational experiment with CPLEX for the UAV assignment problem is presented.Note to Practitioners-FDA is an important generalization of multiresource generalized assignment problem, where customers are flexible in their order size. Manufacturers need to determine the optimal size for each item for maximizing the profit. Here, we consider FDA with addition of: 1) choosing a set of orders from a large set of available orders and 2) setup time between operations of two consecutive orders. As a special case, we formulate the assignment of UAVs as an FDA. The formulation significantly reduces the size of the problem compared to some recent published results. It allows more efficient way to solve the problems.Index Terms-Flexible demand assignment (FDA) problem, unmanned aerial vehicles (UAVs).

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“…First appearing in 1952 [7], the classic assignment problem is to find a one-to-one matching between n tasks and m agents and the objective function is to minimize the total cost. Over the past few decades, the classic assignment problem has been extended and many variations of the assignment problem are proposed, for example, variation in objective function such as maximizing profit [8,9] or minimizing the maximum number of travelling time [10], variation in planning period such as three-dimensional assignment problem [11], multiperiod assignment problems for medical residents [12], multi-period machine assignment [13] or variation in task and resource such as multi-resource generalized assignment problem [14], resource-constrained assignment scheduling [15], assignment problem with seniority and job priority constraints [16] and generalization of multi-resource generalized assignment problem [9].…”

Section: Introductionmentioning

confidence: 99%

A Two-Step Tabu Search Heuristic for Multi-period Multi-site Assignment Problem with Joint Requirement of Multiple Resource Types

Swangnop

Chaovalitwongse

2014

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An assignment problem has been extensively studied and applied in many industries. Variations of assignment problem have been proposed and appeared in literatures for many years. This paper extends the variation of assignment problem in the dimension of task and resource by proposing the joint requirement of multiple resource types in a multi-period multi-site assignment problem. The specific characteristic is that there are many multi-skill resource types and tasks require joint requirement of more than one resource type to operate. An application of this model can be found in healthcare industry, especially in clinic networks or hospital networks, which have many service locations, have many resource types such as doctors, nurses or medical equipments and definitely require more than one resource type for operations. This paper proposes a two-step Tabu search heuristic for multi-period multi-site assignment problem with joint requirement of multiple resource types. The specified neighborhood strategy, short-term memory and long-term memory are designed for the addressed problem in order to generate an efficient move to improve solutions. From computational study, solutions from Tabu search algorithm are compared with optimal solutions from CPLEX, and the result shows that, for small size problems, most solutions are close to optimal solutions (average gap = 2.2%), for medium size problems, the algorithm can provide good solutions in a short time comparing with CPLEX (average gap = 5.8%), and for large size problem, four out of five solutions from the proposed algorithm are better than solutions from CPLEX in a limit of time.

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A note on task assignment of several problems

Cited by 15 publications

References 16 publications

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

On the Flexible Demand Assignment Problems: Case of Unmanned Aerial Vehicles

A Two-Step Tabu Search Heuristic for Multi-period Multi-site Assignment Problem with Joint Requirement of Multiple Resource Types

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