Chaotic Multi-Objective Simulated Annealing and Threshold Accepting for Job Shop Scheduling Problem

The Job Shop Scheduling Problem (JSSP) has enormous industrial applicability. This problem refers to a set of jobs that should be processed in a specific order using a set of machines. For the single-objective optimization JSSP problem, Simulated Annealing is among the best algorithms. However, in Multi-Objective JSSP (MOJSSP), these algorithms have barely been analyzed, and the Threshold Accepting Algorithm has not been published for this problem. It is worth mentioning that the researchers in this area have not reported studies with more than three objectives, and the number of metrics they used to measure their performance is less than two or three. In this paper, we present two MOJSSP metaheuristics based on Simulated Annealing: Chaotic Multi-Objective Simulated Annealing (CMOSA) and Chaotic Multi-Objective Threshold Accepting (CMOTA). We developed these algorithms to minimize three objective functions and compared them using the HV metric with the recently published algorithms, MOMARLA, MOPSO, CMOEA, and SPEA. The best algorithm is CMOSA (HV of 0.76), followed by MOMARLA and CMOTA (with HV of 0.68), and MOPSO (with HV of 0.54). In addition, we show a complexity comparison of these algorithms, showing that CMOSA, CMOTA, and MOMARLA have a similar complexity class, followed by MOPSO.

A Non-Linear-Threshold-Accepting Function Based Algorithm for the Solution of Economic Dispatch Problem

This article introduces a novel heuristic algorithm based on Non-Linear Threshold Accepting Function to solve the challenging non-convex economic dispatch problem. Economic dispatch is a power system management tool; it is used to allocate the total power generation to the generating units to meet the active load demand. The power systems are highly nonlinear due to the physical and operational constraints. The complexity of the resulting non-convex objective cost function led to inabilities to solve the problem by using analytical approaches, especially in the case of large-scale problems. Optimization techniques based on heuristics are used to overcome these difficulties. The Non-Linear Threshold Accepting Algorithm has demonstrated efficiency in solving various instances of static and dynamic allocation and scheduling problems but has never been applied to solve the economic dispatch problem. Existing benchmark systems are used to evaluate the performance of the proposed heuristic. Additional random instances with different sizes are generated to compare the adopted heuristic to the Harmony Search and the Whale Optimization Algorithms. The obtained results showed the superiority of the proposed algorithm in finding, for all considered instances, a high-quality solution in minimum computational time.

Design and Development of Mirnov Coil Sensor for Eddy Currents Experiment on Toroidal Vessel

A Hybrid set of pointers (HA) is used as a measurable technique for gaining inexact answers for combinatorial streamlining inconveniences. The proposed set of policies is a blend of Threshold Accepting (TA) and Hamming take a look at Algorithms (HSA). It consolidates the first-rate strategies of these calculations like global least uniting possessions of TA set of guidelines and fast union price of Hamming take a look at set of pointers. in this paper HA is implemented to put together One eighty level successions, that have suitable advantage difficulty. in this paper HA is utilized to combine One eighty phase arrangements with right gain difficulty. The blanketed groupings have complex signal form and exceedingly excessive to find out and examine with the valuable beneficial asset of a foe's advanced assist Measures (ESMs). The intermingling price of HA is affirmed to be valid