Generally, Job Shop Scheduling Problem (JSSP) is an operational sequencing problem to process n j... more Generally, Job Shop Scheduling Problem (JSSP) is an operational sequencing problem to process n jobs on m machines in a given sequence so as to optimally utilize the resources by complete processing of all jobs in a minimum possible time. JSSP has belongs to the category of NP hard problems where the search space of the problem is (n!) m. Several naturally inspired evolutionary techniques / methods have recently been developed to address these problems to get near optimal solutions in a reasonable time period thus several unsolved / difficulty to solve JSSPs became target for many researchers. Some Traditional Optimization Techniques includes Priority Dispatch Rules, Efficient Methods solvable in polynomial times. Enumerative methods and Mathematical formulation like Linear Programming, Mixed Linear Programming, Lagrangian Relaxation, Branch and Bound and Disjunctive Graph techniques etc. the research has been accelerated with applications of Nontraditional Techniques. Application of Artificial Intelligence, insertion Algorithms, Bottleneck Heuristics, Neural Networks, Expert Systems and Local Search algorithms. Application of Evolutionary Algorithms for scheduling found from mid 80s to till date. Genetic Algorithm, Variation in GAs, PSO, ACO, BCO, Memetic Algorithm, Immune Algorithm and several Hybrid Algorithms. The BFO algorithms, HS algorithms, IWO have been found applied in JSSP in the recent years. More focus on the application of Non Traditional methods for JSSP is increasing compared to traditional techniques. For the same cost and time non traditional methods yield better solutions compared to traditional methods. Hence, in this paper classical evolutionary algorithms namely Invasive weed optimization (IWO), Bacterial Foraging Optimization (BFO) and Music Based Harmony Search principles and fine-tuned the mechanisms to model and solve JSSP. Several Bench Mark instances available in OR library were thoroughly tested to prove the efficiency of the proposed methods by selective and random generation of populations. Two different types of population generations were considered i) Random Population (RP): The initial population is randomly generated and applied to the algorithm procedures and let us call such methods as PSO with RP, HSPO with RP, AIA with RP, HAIA with RP, MBHS with RP, IMBHS with RP, BFO and IWO with RP. ii) Selective Population: The initial Populations are generated using priority dispatching rules. A priority dispatching rule is a simple mathematical formula that, based on some processing parameters, specifies the priority of operations to be executed. 10 initial schedules i.e., populations are generated using 10 commonly used priority dispatching rules given in the Table 1 let us call these methods as
Generally, Job Shop Scheduling Problem (JSSP) is an operational sequencing problem to process n j... more Generally, Job Shop Scheduling Problem (JSSP) is an operational sequencing problem to process n jobs on m machines in a given sequence so as to optimally utilize the resources by complete processing of all jobs in a minimum possible time. JSSP has belongs to the category of NP hard problems where the search space of the problem is (n!) m. Several naturally inspired evolutionary techniques / methods have recently been developed to address these problems to get near optimal solutions in a reasonable time period thus several unsolved / difficulty to solve JSSPs became target for many researchers. Some Traditional Optimization Techniques includes Priority Dispatch Rules, Efficient Methods solvable in polynomial times. Enumerative methods and Mathematical formulation like Linear Programming, Mixed Linear Programming, Lagrangian Relaxation, Branch and Bound and Disjunctive Graph techniques etc. the research has been accelerated with applications of Nontraditional Techniques. Application of Artificial Intelligence, insertion Algorithms, Bottleneck Heuristics, Neural Networks, Expert Systems and Local Search algorithms. Application of Evolutionary Algorithms for scheduling found from mid 80s to till date. Genetic Algorithm, Variation in GAs, PSO, ACO, BCO, Memetic Algorithm, Immune Algorithm and several Hybrid Algorithms. The BFO algorithms, HS algorithms, IWO have been found applied in JSSP in the recent years. More focus on the application of Non Traditional methods for JSSP is increasing compared to traditional techniques. For the same cost and time non traditional methods yield better solutions compared to traditional methods. Hence, in this paper classical evolutionary algorithms namely Invasive weed optimization (IWO), Bacterial Foraging Optimization (BFO) and Music Based Harmony Search principles and fine-tuned the mechanisms to model and solve JSSP. Several Bench Mark instances available in OR library were thoroughly tested to prove the efficiency of the proposed methods by selective and random generation of populations. Two different types of population generations were considered i) Random Population (RP): The initial population is randomly generated and applied to the algorithm procedures and let us call such methods as PSO with RP, HSPO with RP, AIA with RP, HAIA with RP, MBHS with RP, IMBHS with RP, BFO and IWO with RP. ii) Selective Population: The initial Populations are generated using priority dispatching rules. A priority dispatching rule is a simple mathematical formula that, based on some processing parameters, specifies the priority of operations to be executed. 10 initial schedules i.e., populations are generated using 10 commonly used priority dispatching rules given in the Table 1 let us call these methods as
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Papers by Henok Mekonnen