scholarly journals A mixed integer linear programming formulation for low discrepancy consecutive k-sums permutation problem

2017 ◽  
Vol 27 (1) ◽  
pp. 125-132
Author(s):  
Milena Bogdanovic ◽  
Zoran Maksimovic ◽  
Ana Simic ◽  
Jelisavka Milosevic

In this paper, low discrepancy consecutive k-sums permutation problem is considered. A mixed integer linear programing (MILP) formulation with a moderate number of variables and constraints is proposed. The correctness proof shows that the proposed formulation is equivalent to the basic definition of low discrepancy consecutive k-sums permutation problem. Computational results, obtained on standard CPLEX solver, give 88 new exact values, which clearly show the usefulness of the proposed MILP formulation.

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yujian Song ◽  
Ming Xue ◽  
Changhua Hua ◽  
Wanli Wang

In this paper, we investigate the resource-constrained order acceptance and scheduling on unrelated parallel machines that arise in make-to-order systems. The objective of this problem is to simultaneously select a subset of orders to be processed and schedule the accepted orders on unrelated machines in such a way that the resources are not overutilized at any time. We first propose two formulations for the problem: mixed integer linear programming formulation and set partitioning. In view of the complexity of the problem, we then develop a column generation approach based on the set partitioning formulation. In the proposed column generation approach, a differential evolution algorithm is designed to solve subproblems efficiently. Extensive numerical experiments on different-sized instances are conducted, and the results demonstrate that the proposed column generation algorithm reports optimal or near-optimal solutions that are evidently better than the solutions obtained by solving the mixed integer linear programming formulation.


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