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This paper aims to represent a novel framework for optimization of robotic handling from disarray to structure where the products are randomly distributed on a surface, the initial location of the products are known (with the aid of image processing, laser position sensors, etc.) and there is a set of final positions for the products.

Pick‐and‐place is one of the main solutions especially for the food products where the products are prone to damage, have adhesive surfaces and the grippers can be complicated. The aim of this paper is to maximize the utilization of the pick‐and‐place robotic system. In order to do so the handling process is modelled mathematically and the pick‐and‐place problem is formulated based on assignment problem where Hungarian algorithm is utilized to minimize the total distance travelled by the robot. Furthermore, a simulation program is developed to demonstrate the possible improvements of the algorithm in comparison with the existing algorithms.

Utilizing the proposed algorithm can significantly increase the utilization of robots in the pick‐and‐place operation.

The new optimization algorithm can be applied to any industry with pick‐and‐place where time efficiency and maximum utilization matters.

This paper aims to introduce and identify a new 3D handling operation (bin picking) for natural discrete food products using food categorisation.

The research shows a new food categorisation and the relation between food ordering processes and food categories. Bin picking in the food industry needs more flexible vision software compared to the manufacturing industry in order to decrease the degree of disarray of food products and transfer them into structure.

It has been shown that there are still manual operated ordering processes in food industry such as bin picking; it just needs new ideas of image processing algorithms such as active shape models (ASMs) on its development in order to recognise the highly varying shapes of food products.

This research was aimed at locating a new ordering process and proving a new principle, but for practical implementation this bin picking solution needs to be developed and tested further.

Identifying new ordering processes via food categorisation is unique and applying ASMs to bin picking opens a new industrial sector (food industry) for 3D handling.

This chapter demonstrates that women challenge oppressive gender relations by engaging in active agency at different levels. Iranian women’s struggles for gender equality show a critical consciousness of the politics of local male domination and an indigenous contestation of the cultural practices which sanction injustices against women.

This chapter is based on the findings and analysis of the book, Women, Power and Politics in 21st Century in Iran. It is the result of the political and personal experiences of a number of Iranian women academics, journalist and activists who live and work in Iran.

Based on the updated findings and new statistical data, this chapter argues that women, despite their high level of education and activism, continue to face gender inequality, in particular in the sphere of employment.

This chapter is intended to counter the often inaccurate and misleading impressions put forward by the media, politicians and some academics in the West when they talk about Iranian women. Within the broader feminist theoretical positioning, the aim of this chapter is to contribute to the debate on essentialism and the stereotype of Iranian women as submissive Muslim women without agency.

Feminist knowledge production is diverse. Nonetheless, consideration of the historical and geographical locations of feminist knowledge production is vital to our understanding of the complex processes of women’s liberation. Thus, Iranian women’s voices are important to what is traditionally understood as feminism.