Preemptive Scheduling, Linear Programming and Network Flows

1984 ◽  
Vol 5 (1) ◽  
pp. 11-20 ◽  
Author(s):  
D. de Werra
Keyword(s):  
Linear Programming ◽  
Network Flows ◽  
Preemptive Scheduling

Preemptive scheduling with transportation delays between machines

2020 ◽  
Vol 15 (3) ◽  
pp. 829-847
Author(s):  
Ryma Zineb Badaoui ◽  
Mourad Boudhar ◽  
Mohammed Dahane
Keyword(s):  
Linear Programming ◽  
Neighborhood Search ◽  
Preemptive Scheduling ◽  
Scheduling Problem ◽  
Programming Formulation ◽  
Content Type ◽  
Decision Variables ◽  
Linear Programming Formulation ◽  
Local Search Strategy ◽  
Two Stages

Purpose This paper studies the preemptive scheduling problem of independent jobs on identical machines. The purpose of this paper is to minimize the makespan under the imposed constraints, namely, the ones that relate the transportation delays which are required to transport a preempted job from one machine to another. This study considers the case when the transportation delays are variable. Design/methodology/approach The contribution is twofold. First, this study proposes a new linear programming formulation in real and binary decision variables. Then, this study proposes and implements a solution strategy, which consists of two stages. The goal of the first stage is to obtain the best machines order using a local search strategy. For the second stage, the objective is to determine the best possible sequence of jobs. To solve the preemptive scheduling problem with transportation delays, this study proposes a heuristic and two metaheuristics (simulated annealing and variable neighborhood search), each with two modes of evaluation. Findings Computational experiments are presented and discussed on randomly generated instances. Practical implications The study has implications in various industrial environments when the preemption of jobs is allowed. Originality/value This study proposes a new linear programming formulation for the problem with variable transportation delays as well as a corresponding heuristic and metaheuristics.

Overlay Multicast Optimization: IBM ILOG CPLEX

2012 ◽  
Vol 58 (4) ◽  
pp. 381-388 ◽  
Author(s):  
Michał Kucharzak ◽  
Dawid Zydek ◽  
Iwona Poźniak-Koszałka
Keyword(s):  
Linear Programming ◽  
Network Flows ◽  
Academic Research ◽  
Mixed Integer ◽  
Overlay Multicast ◽  
Complex Optimization ◽  
Linear Problems ◽  
Global Parameters

Abstract IBM ILOG CPLEX Optimization Studio delivers advanced and complex optimization libraries that solve linear programming (LP) and related problems, e.g., mixed integer. Moreover, the optimization tool provides users with its Academic Research Edition, which is available for teaching and noncommercial research at no-charge. This paper describes the usage of CPLEX C++ API for solving linear problems and, as an exhaustive example, optimization of network flows in overlay multicast is taken into account. Applying continuous and integral variables and implementing various constraints, including equations and inequalities, as well as setting some global parameters of the solver are presented and widely explained.

Linear Programming and Network Flows

1978 ◽  
Vol 29 (5) ◽  
pp. 510
Author(s):  
C. R. Sergeant ◽  
Mokhtar S. Bazaraa ◽  
John J. Jarvis
Keyword(s):  
Linear Programming ◽  
Network Flows
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