Peak Demand Minimization via Sliced Strip Packing

by   Max A. Deppert, et al.

We study Nonpreemptive Peak Demand Minimization (NPDM) problem, where we are given a set of jobs, specified by their processing times and energy requirements. The goal is to schedule all jobs within a fixed time period such that the peak load (the maximum total energy requirement at any time) is minimized. This problem has recently received significant attention due to its relevance in smart-grids. Theoretically, the problem is related to the classical strip packing problem (SP). In SP, a given set of axis-aligned rectangles must be packed into a fixed-width strip, such that the height of the strip is minimized. NPDM can be modeled as strip packing with slicing and stacking constraint: each rectangle may be cut vertically into multiple slices and the slices may be packed into the strip as individual pieces. The stacking constraint forbids solutions where two slices of the same rectangle are intersected by the same vertical line. Nonpreemption enforces the slices to be placed in contiguous horizontal locations (but may be placed at different vertical locations). We obtain a (5/3+ϵ)-approximation algorithm for the problem. We also provide an asymptotic efficient polynomial-time approximation scheme (AEPTAS) which generates a schedule for almost all jobs with energy consumption (1+ϵ)OPT. The remaining jobs fit into a thin container of height 1. The previous best for NPDM was 2.7 approximation based on FFDH [Ranjan et al. 2015]. One of our key ideas is providing several new lower bounds on the optimal solution of a geometric packing, which could be useful in other related problems. These lower bounds help us to obtain approximative solutions based on Steinberg's algorithm in many cases. In addition, we show how to split schedules generated by the AEPTAS into few segments and to rearrange the corresponding jobs to insert the thin container mentioned above.


page 1

page 2

page 3

page 4


Improved Pseudo-Polynomial-Time Approximation for Strip Packing

We study the strip packing problem, a classical packing problem which ge...

Tight Approximation Algorithms for Two Dimensional Guillotine Strip Packing

In the Strip Packing problem (SP), we are given a vertical half-strip [0...

Approximation Algorithms for Demand Strip Packing

In the Demand Strip Packing problem (DSP), we are given a time interval ...

Tight Approximation Algorithms for Geometric Bin Packing with Skewed Items

In the Two-dimensional Bin Packing (2BP) problem, we are given a set of ...

Constant Factor Approximation Algorithm for Weighted Flow Time on a Single Machine in Pseudo-polynomial time

In the weighted flow-time problem on a single machine, we are given a se...

Packing squares independently

Given a set of squares and a strip of bounded width and infinite height,...

A 12/7-approximation algorithm for the discrete Bamboo Garden Trimming problem

We study the discrete Bamboo Garden Trimming problem (BGT), where we are...

Please sign up or login with your details

Forgot password? Click here to reset