The multiplicity difference correlators between two well-separated bins in high-energy heavy-ion collisions are studied as a means to detect evidence of a first-order quark-hadron phase transition. Analytical expressions for the scaled factorial moments of multiplicity difference distribution are obtained for small bin size δ with mean multiplicity in the bin s ≤ 1.0 within Ginzburg-Landau desc...

We consider the Variable Size Bin Packing Problem with Fixed Costs, a generalization of the well-known bin packing problem where a set of items must be packed within a set of heterogeneous bins characterized by possibly different volumes and fixed costs. The objective of the problem is to select the bins to pack all items while minimizing the total cost incurred for the selected bins. We presen...

The bin packing game is a cooperative N -person game, where the set of players consists of k bins, each has capacity 1 and n items of sizes a1, a2, ⋅ ⋅ ⋅ , an, w.l.o.g, we assume 0 ≤ ai ≤ 1 for all 1 ≤ i ≤ n. The value function of a coalition of bins and items is the maximum total size of items in the coalition that can be packed into the bins of the coalition. A typical question of the bin pac...

This comprehensive work explores the research performed inoptimization of the collection bin and in recycle bin location-allocation issues in solidwaste management. Although the collection phase of solid waste management accountsfor a significant proportion of the municipal budget, it has attracted only limitedattention of the researchers. Optimization of the collection bin and recycle bin loca...

In this paper, we introduce a generalization of the vector bin packing problem, where the bins have variable sizes. This generalization can be used to model virtual machine placement problems. In particular, we study the machine reassignment problem. We propose several greedy heuristics for the variable size vector bin packing problem and show that they are flexible and can be adapted to handle...

The bin packing problem is one of the classical NP-hard optimization problems. In this paper, we present a simple generic approach for obtaining new fast lower bounds, based on dual feasible functions. Worst-case analysis as well as computational results show that one of our classes clearly outperforms the previous best “economical” lower bound for the bin packing problem by Martello and Toth, ...

We consider the following stochastic bin packing process: the items arrive continuously over time to a server and are packed into bins of unit size according to an online algorithm. The unpacked items form a queue. The items have random sizes with symmetric distribution. Our first contribution identifies some monotonicity properties of the queueing system that allow to derive bounds on the queu...

We study the following variant of the bin packing problem. We are given a set of items, where each item has a (non-negative) size and a color. We are also given an integer parameter k, and the goal is to partition the items into a minimum number of subsets such that for each subset S in the solution, the total size of the items in S is at most 1 (as in the classical bin packing problem) and the...