A Novel Pareto-Based Meta-Heuristic Algorithm to Optimize Multi-Facility Location-Allocation Problem
نویسنده
چکیده
This article proposes a novel Pareto-based multiobjective meta-heuristic algorithm named non-dominated ranking genetic algorithm (NRGA) to solve multi-facility location-allocation problem. In NRGA, a fitness value representing rank is assigned to each individual of the population. Moreover, two features ranked based roulette wheel selection including select the fronts and choose solutions from the fronts, are utilized. The proposed solving methodology is validated using several examples taken from the specialized literature. The performance of our approach shows that NRGA algorithm is able to generate true and well distributed Pareto optimal solutions. Keywords—Non-dominated ranking genetic algorithm, Pareto solutions, Multi-facility location-allocation problem.
منابع مشابه
A New Hybrid Algorithm to Optimize Stochastic-fuzzy Capacitated Multi-Facility Location-allocation Problem
Facility location-allocation models are used in a widespread variety of applications to determine the number of required facility along with the relevant allocation process. In this paper, a new mathematical model for the capacitated multi-facility location-allocation problem with probabilistic customer's locations and fuzzy customer’s demands under the Hurwicz criterion is proposed. Thi...
متن کاملMulti-objective evolutionary algorithms for a preventive healthcare facility network design
Preventive healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. In this paper, a bi-objective mathematical model is proposed to design a network of preventive healthcare facilities so as to minimize total travel and waiting time as well as establishment and staffing cost. Moreover, each facility acts as M/M/1 queuin...
متن کاملA Novel Adapted Multi-objective Meta-heuristic Algorithm for a Flexible Bi-objective Scheduling Problem Based on Physics Theory
We relax some assumptions of the traditional scheduling problem and suggest an adapted meta-heuristic algorithm to optimize efficient utilization of resources and quick response to demands simultaneously. We intend to bridge the existing gap between theory and real industrial scheduling assumptions (e.g., hot metal rolling industry, chemical and pharmaceutical industries). We adapt and evalua...
متن کاملEvaluating the Effectiveness of Integrated Benders Decomposition Algorithm and Epsilon Constraint Method for Multi-Objective Facility Location Problem under Demand Uncertainty
One of the most challenging issues in multi-objective problems is finding Pareto optimal points. This paper describes an algorithm based on Benders Decomposition Algorithm (BDA) which tries to find Pareto solutions. For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how P...
متن کاملTwo Strategies Based on Meta-Heuristic Algorithms for Parallel Row Ordering Problem (PROP)
Proper arrangement of facility layout is a key issue in management that influences efficiency and the profitability of the manufacturing systems. Parallel Row Ordering Problem (PROP) is a special case of facility layout problem and consists of looking for the best location of n facilities while similar facilities (facilities which has some characteristics in common) should be arranged in a row ...
متن کامل