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Amir Azaron
Researcher at Kwantlen Polytechnic University
Publications - 64
Citations - 1925
Amir Azaron is an academic researcher from Kwantlen Polytechnic University. The author has contributed to research in topics: Queueing theory & Stochastic programming. The author has an hindex of 26, co-authored 64 publications receiving 1763 citations. Previous affiliations of Amir Azaron include Linköping University & Simon Fraser University.
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A multi-objective stochastic programming approach for supply chain design considering risk
TL;DR: In this paper, a multi-objective stochastic programming approach for supply chain design under uncertainty is developed, which includes the minimization of the sum of current investment costs and the expected future processing, transportation, shortage and capacity expansion costs.
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Solving a dynamic cell formation problem using metaheuristics
TL;DR: This research, a nonlinear integer model of CF is first given and then solved by GA, SA and TS, and the results are compared with the optimal solution and the efficiency of the proposed algorithms is discussed.
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A genetic algorithm approach for the time-cost trade-off in PERT networks
TL;DR: A multi-objective model for the time-cost trade-off problem in PERT networks with generalized Erlang distributions of activity durations, using a genetic algorithm, and compares the genetic algorithm results against the results of a discrete-time approximation method for solving the original optimal control problem.
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A hybrid method for solving stochastic job shop scheduling problems
TL;DR: A hybrid method using a neural network approach to generate initial feasible solutions and then a simulated annealing algorithm to improve the quality and performance of the initial solutions in order to produce the optimal/near-optimal solution.
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Dynamic shortest path in stochastic dynamic networks: Ship routing problem
Amir Azaron,Farhad Kianfar +1 more
TL;DR: In this article, the authors apply stochastic dynamic programming (SDP) to find the dynamic shortest path from the source node to the sink node in a continuous time Markov process, where the arc lengths are independent random variables with exponential distributions.