This paper presents a multi-objective mathematical model which aims to optimize and harmonize supply chain reduce costs, improve quality, achieve competitive advantage position using meta-heuristic algorithms. The purpose of optimization in this field is increase quality customer satisfaction production time related prices. present research simultaneously optimized the multi-product multi-perio...

Alzheimer’s disease (AD) is a neurodegenerative that affects large number of people across the globe. Even though AD one most commonly seen brain disorders, it difficult to detect and requires categorical representation features differentiate similar patterns. Research into more complex problems, such as detection, frequently employs neural networks. Those approaches are regarded well-understoo...

Objective: The objective of this systematic review and meta-analysis was to assess the efficacy exercise in neuropathic pain following traumatic spinal cord injuries.Methods: search conducted MEDLINE, Embase, Scopus, Web Science by end 2022. Two independent researchers included articles based on inclusion exclusion criteria. A standardized mean difference calculated for each data they were pool...

This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on text clustering applications and highlights its main procedures. These Artificial Intelligence (AI) are recognized as promising swarm intelligence methods due to their successful ability solve machine learning problems, especially problems. reviews all relevant literature meta-heuristic-based application...

Objective To examine the safety of using aliskiren combined with agents used to block the renin-angiotensin system. Design Systematic review and meta-analysis of randomised controlled

Objective To assess the effectiveness of physiotherapy compared with no intervention in patients with Parkinson’s disease. Design Systematic review and meta-analysis of randomised controlled

A new bi-objective genetic programming (BioGP) technique has been developed for meta-modeling and applied in a chromatographic separation process using a simulated moving bed (SMB) process. The BioGP technique initially minimizes training error through a single objective optimization procedure and then a trade-off between complexity and accuracy is worked out through a genetic algorithm based b...

The solutions used to solve bi-level congestion pricing problems are usually based on heuristic network optimization methods which may not be able to find the best solution for these type of problems. The application of meta-heuristic methods can be seen as viable alternative solutions but so far, it has not received enough attention by researchers in this field. Therefore, the objective of thi...

This paper considers a non-identical parallel machine scheduling problem with sequence and machine dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of each machine to minimize makespan. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain opt...