A class of greedy algorithms for the generalized assignment problem

Romeijn, H. Edwin; Morales, Dolores Romero

doi:10.1016/s0166-218x(99)00224-3

Cited by 72 publications

(39 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since our purpose lies in the coverage of the rest video content set rather than maximizing the objective value, we adopt a greedy method for GAP in [7]. The algorithm is outlined in Algorithm 2, in which we define a desirability function, and iteratively assign the video content with the most desirability to the best node till no video content clip is left.…”

Section: )mentioning

confidence: 99%

Video Contents Prior Storing Server For Lte Networks

Tsang¹,

Fun²

2015

IJWMN

View full text Add to dashboard Cite

show abstract

Section: )mentioning

confidence: 99%

Video Contents Prior Storing Server For Lte Networks

Tsang¹,

Fun²

2015

IJWMN

View full text Add to dashboard Cite

show abstract

“…They use the technique based on the combinatorial translation of any algorithm for the knapsack problem into an approximation algorithm. Romeijn and Morales in [12] propose greedy heuristics based on the approach for the multi-knapsack problem. Many genetic algorithms have been used for solving the generalized assignment problem, e.g., [13]- [15].…”

Section: International Journal Of Applied Physics and Mathematicsmentioning

confidence: 99%

Efficient Heuristics for Single-Source Transportation Problems

Pongchairerks¹

2014

IJAPM

View full text Add to dashboard Cite

This paper develops two efficient heuristics to solve the single-source transportation problem, i.e. the special class of the transportation problem where each customer must be served by only one supplier. The proposed heuristics are both started by simplifying the problem into the simpler transportation problem where each customer requires exact one product lot. Then, the first heuristic solves the simplified problem using the transportation algorithm while the second heuristic solves it using the assignment algorithm. The heuristics return an optimal solution or a near-optimal solution for every benchmark instance.

show abstract

“…Then, z j is assigned to a server s i with the highest value of µ ij and with sufficient resource capacity. This procedure is similar to the approach used to solve the well-known Generalized Assignment Problem [22].…”

Section: Greedy Assignment Of Zones (Grez)mentioning

confidence: 99%