A method for finding the set of non-dominated vectors for multiple objective integer linear programs

2004 ◽  
Vol 158 (1) ◽  
pp. 46-55 ◽  
Author(s):  
John Sylva ◽  
Alejandro Crema
Author(s):  
Andrew Palmer Wheeler

PurposeThe purpose of this paper is to illustrate the use of the p-median model to construct optimal patrol areas. This can improve both time spent traveling to calls, as well as equalize call load between patrol areas.Design/methodology/approachThe paper provides an introduction to the use of integer linear programs to create optimal patrol areas, as many analysts and researchers in the author’s field will not be familiar with such models. The analysis then introduces a set of linear constraints to the p-median problem that are applicable to police agencies, such as constraining call loads to be equal and making patrol areas geographically contiguous.FindingsThe analysis illustrates the technique on simplified simulated examples. The analysis then demonstrates the utility of the technique by showing how patrol areas in Carrollton, TX can be made both more efficient and equalize the call loads given the same number of patrol beats as currently in place.Originality/valueUnlike prior applications of creating patrol areas, this paper introduces linear constraints into the p-median problem, making it much easier to solve than programs that have non-linear or multiple objective functions. Supplementary code using open source software is also provided, allowing other analysts or researchers to apply the model to their own data.


Author(s):  
Klaus Jansen ◽  
Kim-Manuel Klein ◽  
Marten Maack ◽  
Malin Rau

AbstractInteger linear programs of configurations, or configuration IPs, are a classical tool in the design of algorithms for scheduling and packing problems where a set of items has to be placed in multiple target locations. Herein, a configuration describes a possible placement on one of the target locations, and the IP is used to choose suitable configurations covering the items. We give an augmented IP formulation, which we call the module configuration IP. It can be described within the framework of n-fold integer programming and, therefore, be solved efficiently. As an application, we consider scheduling problems with setup times in which a set of jobs has to be scheduled on a set of identical machines with the objective of minimizing the makespan. For instance, we investigate the case that jobs can be split and scheduled on multiple machines. However, before a part of a job can be processed, an uninterrupted setup depending on the job has to be paid. For both of the variants that jobs can be executed in parallel or not, we obtain an efficient polynomial time approximation scheme (EPTAS) of running time $$f(1/\varepsilon )\cdot \mathrm {poly}(|I|)$$ f ( 1 / ε ) · poly ( | I | ) . Previously, only constant factor approximations of 5/3 and $$4/3 + \varepsilon $$ 4 / 3 + ε , respectively, were known. Furthermore, we present an EPTAS for a problem where classes of (non-splittable) jobs are given, and a setup has to be paid for each class of jobs being executed on one machine.


2014 ◽  
Vol 233 (3) ◽  
pp. 459-473 ◽  
Author(s):  
Xiaobo Li ◽  
Karthik Natarajan ◽  
Chung-Piaw Teo ◽  
Zhichao Zheng

1999 ◽  
Vol 119 (3) ◽  
pp. 671-677
Author(s):  
Gilbert Laporte ◽  
Frédéric Semet

1999 ◽  
Vol 11 (1) ◽  
pp. 63-77 ◽  
Author(s):  
Olivier Guieu ◽  
John W. Chinneck

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