The lower bound on First-Fit's accommodating ratio, for the Unit Price Bin Packing problem, is improved to 5=8.

In the variable-sized online bin packing problem, one has to assign items to bins one by one. The bins are drawn from some xed set of sizes, and the goal is to minimize the sum of the sizes of the bins used. We present the rst unbounded space algorithms for this problem. We also show the rst lower bounds on the asymptotic performance ratio. The case where bins of two sizes, 1 and 2 (0; 1), are ...

Online Bin Stretching is a semi-online variant of bin packing in which the algorithm has to use the same number of bins as an optimal packing, but is allowed to slightly overpack the bins. The goal is to minimize the amount of overpacking, i.e., the maximum size packed into any bin. We give an algorithm for Online Bin Stretching with a stretching factor of 1.5 for any number of bins. We build o...

This paper deals to solve the one dimensional bin-packing problem with conflicts. The conflicts are represented by a graph whose nodes are the items, and adjacent items cannot be packed into the same bin. We propose an adaptation of Minimum Bin Slack heuristic also with a combination of heuristics based on the uses of the classical bin-packing methods to packing items of maximal-stable-subsets ...

This paper describes the application of an unscented Kalman filter to a coal runof-mine bin. A dynamic model of the bin is derived using the principle of mass conservation. The dynamic model is nonlinear with unknown parameters that are identified using actual plant production data. The identified dynamic model is used by an unscented Kalman filter to update the states of the system to improve ...

We formally define multi-resource bin packing, a generalization of conventional bin packing, and develop an algorithm called Reordering Grouping Genetic Algorithm (RGGA) to solve this problem. Multi-resource bin packing can be applied to different problems, such as placing virtual machines onto servers. We first test RGGA on conventional bin packing problems and show that it yields excellent re...

Online Bin Stretching is a semi-online variant of bin packing in which the algorithm has to use the same number of bins as the optimal packing, but is allowed to slightly overpack the bins. The goal is to minimize the amount of overpacking, i.e., the maximum size packed into any bin. We give an algorithm for Online Bin Stretching with a stretching factor of 1.5 for any number of bins. We also s...

The Internet of Things (IoT) paradigm plays a vital role for improving smart city applications by tracking and managing processes in real-time. One the most significant issues associated with is solid waste management, which has negative impact on our society’s health environment. traditional management process begins created residents disposed garbage bins at source. Municipal department truck...

We consider a variant of bin packing calledmultiple-choice vector bin packing. In this problem we are given a set of n items, where each item can be selected in one of several D-dimensional incarnations. We are also given T bin types, each with its own cost and D-dimensional size. Our goal is to pack the items in a set of bins of minimum overall cost. The problem is motivated by scheduling in n...

The bin-packing problem is a well known NP-Hard optimisation problem, and, over the years, many heuristics have been developed to generate good quality solutions. This paper outlines a genetic programming system which evolves a heuristic that decides whether to put a piece in a bin when presented with the sum of the pieces already in the bin and the size of the piece that is about to be packed....