In this paper, seven different metaheuristic optimization algorithms developed between 2005 and 2012 are applied to optimize the robot trajectory for a three-revolute (3R) robotic arm. These algorithms include the artificial bee colony (ABC) algorithm, biogeography-based optimization, gravitational search algorithm, cuckoo search algorithm (CS), firefly algorithm, bat algorithm, and teaching-learning-based optimization (TLBO). This work presents the optimization problem with the objective to plan a trajectory, which can minimize joint travelling time, joint travelling distance, and total joint Cartesian lengths, simultaneously. Nine different design variables are considered for the intermediate joint angles, joint velocities, the end-effector angle for the final configuration, the time from initial to intermediate configuration, and the time from intermediate to final configuration. Two different experiments are conducted to investigate the effect of different considered metaheuristics: 1) for the free workspace and 2) for the workspace with obstacle. All these algorithms are compared based on the algorithm ability to find the best solutions, mean solutions, standard deviation, computational effort, and the convergence of the solutions. Statistical investigation is also performed by using the Friedman rank test and the Holm-Sidak multiple comparison t-test to check the significance of the algorithm for its suitability to the robot trajectory optimization problems. The results show the significance of TLBO, ABC, and CS for the robot trajectory optimization problems. Index Terms-Artificial bee colony (ABC) algorithm, bat algorithm (BA), biogeography-based optimization (BBO), cuckoo search algorithm (CS), firefly algorithm (FA), gravitational search algorithm (GSA), obstacle existence, optimization, robot trajectory, teaching-learning-based optimization (TLBO).

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In the present work, a multiobjective heat transfer search (MOHTS) algorithm is proposed and investigated for thermo‐economic and thermodynamic optimization of a plate–fin heat exchanger (PFHX). Heat exchanger effectiveness and total annual cost (TAC) are considered as thermo‐economic objective functions. Similarly, entropy generation rate and heat exchanger effectiveness are considered as thermodynamic objective functions. Six design variables including flow length of cold and hot streams, no flow length, fin height, fin pitch, and fin offset length are considered as decision variables. Effectiveness and accuracy of the proposed algorithm are evaluated by analyzing application examples of a PFHX. The results obtained using the proposed algorithm for thermo‐economic considerations are compared with the available results of NSGA‐II and TLBO in the literature. Results show that 3.56% to 10.29% reductions in TAC with 0.48% to 0.81% higher effectiveness are observed using the proposed approach compared to TLBO and NSGA‐II approaches. Additionally, the distribution of each design variable in its allowable range is also shown for thermo‐economic consideration to identify the level of conflict on objective functions. The sensitivity analyses of design variables on the objective functions value are also performed in detail.