Makespan minimizing on multiple travel salesman problem with a learning effect of visiting time

-The multiple traveling salesman problem (MTSP) involves the assignment and sequencing procedure simultaneously. The assignment of a set of nodes to each visitors and determining the sequence of visiting of nodes for each visitor. Since specific range of process is needed to be carried out in nodes in commercial environment, several factors associated with routing problem are required to be taken into account. This research considers visitors’ skill and category of customers which can affect visiting time of visitors in nodes. With regard to learning-by-doing, visiting time in nodes can be reduced. And different class of customers which are determined based on their potential purchasing of power specifies that required time for nodes can be vary. So, a novel optimization model is presented to formulate MTSP, which attempts to ascertain the optimum routes for salesmen by minimizing the makespan to ensure the balance of workload of visitors. Since this problem is an NP-hard problem, for overcoming the restriction of exact methods for solving practical large-scale instances within acceptable computational times. So, Artificial Immune System (AIS) and the Firefly (FA) metaheuristic algorithm are implemented in this paper and algorithms parameters are calibrated by applying Taguchi technique. The solution methodology is assessed by an array of numerical examples and the overall performances of these metaheuristic methods are evaluated by analyzing their results with the optimum solutions to suggested problems. The results of statistical analysis by considering 95% confidence interval for calculating average relative percentage of deviation (ARPD) reveal that the solutions of proposed AIS algorithm has less variation and Its’ confidence interval of closer than to zero with no overlapping with that of FA. Although both proposed meta-heuristics are effective and efficient in solving small-scale problems, in medium and large scales problems, AIS had a better performance in a shorter average time. Finally, the applicability of the suggested pattern is implemented in a case study in a specific company, namely Kalleh

Heuristic approaches to address vehicle routing problem in the Iot-based waste management system

Nowadays, population growth and urban development lead to having an efficient waste management system (WMS) based on recent advances and trends. Alongside all functions and procedures in these systems, the waste collection plays a significant role. This study proposes a two-echelon WMS to minimize operational costs and environmental impact by utilizing the industry 4.0 concept. Both models utilize modern traceability Internet of Thing-based devices to compare real-time information of waste level in bins and separation centers with the threshold waste level (TWL) parameter. The first model optimizes the operational cost and Co2 emission of collecting waste from bins to the separation center by considering the time windows. A capacitated vehicle routing problem is designed as a later model-based to minimize the cost of waste transferring to recycling centers. In addition, to find the optimal solution, recent meta-heuristic algorithms are employed, and several novel heuristics based on the problem's specifications are developed. Furthermore, the developed heuristics methods are utilized to generate the initial feasible solutions in meta-heuristics and compared with random ones. The performance of the proposed algorithms is probed, and Best Worst Method (BWM) is applied to rank the algorithms based on relative percentage deviation, relative deviation index and hitting time

The influence of m-aminobenzoic acid on electrochemical synthesis and behavior of poly(aniline-co-(m-aminobenzoic acid)

Poly(aniline-co-(m-aminobenzoic acid)) was synthesized electrochemically at graphite electrode under galvanostatic conditions. Aqueous electrolyte for synthesis was consisted of HCl and different amount of aniline and m-aminobenzoic acid. The presence of the meta positioned carboxylic group in m-aminobenzoic acid influenced higher co-polymerization potential, different morphology and electrochemical behavior of copolymers compared to polyaniline. Electrochemical activity is achieved by proton exchange in neutral environment that can result in a faster charge/discharge process, which is in the case of PANI limited by slow anion exchange, making this material promising for consideration in super-capacitors and in biological system