Assignment problem

About: Assignment problem is a research topic. Over the lifetime, 7588 publications have been published within this topic receiving 172820 citations. The topic is also known as: marriage problem.

BetaDock: Shape-Priority Docking Method Based on Beta-Complex

Abstract: This paper presents an approach and a software, BetaDock, to the docking problem by putting the priority on shape complementarity between a receptor and a ligand. The approach is based on the theory of the β-complex. Given the Voronoi diagram of the receptor whose topology is stored in the quasi-triangulation, the β-complex corresponding to water molecule is computed. Then, the boundary of the β-complex defines the β-shape which has the complete proximity information among all atoms on the receptor boundary. From the β-shape, we first compute pockets where the ligand may bind. Then, we quickly place the ligand within each pocket by solving the singular value decomposition problem and the assignment problem. Using the conformations of the ligands within the pockets as the initial solutions, we run the genetic algorithm to find the optimal solution for the docking problem. The performance of the proposed algorithm was verified through a benchmark test and showed that BetaDock is superior to a popular docking software AutoDock 4.

A joint quay crane assignment and scheduling problem: formulation, solution algorithm and computational results

Abstract: Quay cranes constitute a significant determinant of container handling efficiency and for this reason the quay crane assignment problem (QCAP) and the quay crane scheduling problem (QCSP) have received great attention in research streams. However, these interdependent problems are usually solved sequentially, due to the high complexity of integration, leading to a potentially inefficient utilization of resources. This paper presents a simple approach for the integrated quay crane assignment and scheduling problem (QCASP), by transforming it into a crane-to-bay assignment problem, and develops a Lagrangian relaxation algorithm to solve it. In order to ensure feasibility, a restoration technique is also developed and this Lagrangian relaxation based heuristic is evaluated as a whole. The choice of constraints to be relaxed is justified and the sub- and master problems are derived. The relaxed problem is solved using the constraint generation method and computational results are conducted in order to evaluate the performance of the Lagrangian heuristic, in terms of computational time, Lagrangian bounds and gaps.

A path-based traffic assignment algorithm based on the TRANSYT traffic model

Abstract: This paper presents a path-based traffic assignment formulation and its solution algorithm for solving an asymmetric traffic assignment problem based on the TRANSYT traffic model, a well-known procedure to determine the queues and delays in a signal-controlled network with explicit considerations of the signal co-ordination effects and platoon dispersion on the streets. The solution algorithm employs a Frank–Wolfe method to identify the descent direction at each iteration, which requires the input of the derivatives information. A post-simulation sensitivity analysis is developed to estimate the derivatives in the TRANSYT traffic model. Good agreement of results with the values determined by numerical differentiation is obtained. Using these derivatives information, the Frank–Wolfe method shows a good convergence behavior to the equilibrium solution. Comparison with other methods is also discussed in a numerical example to demonstrate the effectiveness of the proposed methodology.

Social-Aware Data Collection Scheme Through Opportunistic Communication in Vehicular Mobile Networks

Abstract: To enable the intelligent management of Smart City and improve overall social welfare, it is desirable for the status of infrastructures detected and reported by intelligent devices embedded in them to be forwarded to the data centers. Using “SCmules” such as taxis, to opportunistically communicate with intelligent devices and collect data from the sparse networks formed by them in the process of moving is an economical and effective way to achieve this goal. In this paper, the social welfare data collection paradigm SWDCP-SCmules data collection framework is proposed to collect data generated by intelligent devices and forward them to data centers, in which “SCmules” are data transmitters picking up data from nearby intelligent devices and then store-carry-forwarding them to nearby data centers via short-range wireless connections in the process of moving. Because of the storage limitations, “SCmules” need to weigh the value of data and select some less valuable data to discard when necessary. To quantify the value of data and find a well-performed selection strategy, the concept of priority is introduced to the SWDCP-SCmules scheme, and then, the simulated annealing for priority assignment SA-PA algorithm is proposed to guide the priority assignment. The SA-PA algorithm is a universal algorithm that can improve the performance of SWDCP-SCmules scheme by finding better priority assignment with respect to various optimization targets, such as maximizing collection rate or minimizing redundancy rate, in which priority assignment problem is converted into an optimization problem and simulated annealing is used to optimize the priority assignment. From the perspective of machine learning, the process of optimization is equal to automatically learn social-aware patterns from past GPS trajectory data. Experiments based on real GPS trajectory data of taxis in Beijing are conducted to show the effectiveness and efficiency of SWDCP-SCmules scheme and SA-PA algorithm.

Auction based resource allocation in wireless systems

Abstract: Systems and methods to assign one or more resources in a multi-user cellular Orthogonal Frequency-Division Multiple Access (OFDMA) uplink includes specifying a resource allocation problem for one or more resources; converting the resource allocation problem into an assignment problem; solving the assignment problem through an auction; and allocating one or more resources to cellular users to maximize a system utility.