Purpose: Order picking operation is one of the most well-known labor and cost intensive internal logistics processes. Withdrawal of the order in response to customer need is defined in order to collect a set of orders from storage zone in the shortest possible time. The purpose of this research is to provide a scientific and practical basis considering the constraints that enforce to achieve an acceptable level of performance in order picking systems. This is done by building a Mixed Integer Linear Programming (MILP) formulation and developing an adapted solution method suited to the structure of the problem Methodology: First, by reviewing the literature in the field of order picking systems, sufficient knowledge has been obtained at the operational level, and with emphasis on warehouse management constraints, a MILP formulation is proposed by integrating order batching and Picker routing. After validating the model and solving it through GAMS software, due to the nature of the problem, which is an NP-hard type, the problem is solved with an efficient algorithm, which is a grouping version of the league championship algorithm, and the results are compared. To develop the algorithm, operators are fit to the specific structure of the problem, i. e., the assignment of orders (items) to order Pickers (groups) Findings: Developing a multi-period MILP formulation for multi-trip Picker routing, assuming for the first time the possibility of product replenishment and limited access to Pickers. For large-scale problem instances, the league championship algorithm is used. The results indicate the effective capability and efficiency of this algorithm for solving large test problem instances. Originality/Value: The issue of multi-period order picking and multi-trip routing of Pickers is considered for the first time ‎in this paper. Because of the limited number of Pickers, this must be taken into account in modeling. ‎The assumption of product replenishment is also considered for the first time in this article and its ‎modeling has been done. In this way, orders enter the warehouse over time, during different periods, ‎and are placed in a predetermined positions. The limited access to Pickers in each period is also ‎discussed for the first time in this paper. Finally, the objective function of minimizing the total ‎tardiness, which is in line with the needs of the industry, is also introduced in this paper. Regarding the ‎solution method, a league championship metaheuristic algorithm is presented which takes into ‎account the problem structure (which corresponds to the structure of grouping problems) and ‎solution generation operators have been developed to maintain the new solution. ‎

Aims: Patient experience, along with clinical performance and safety, is known as a critical criterion for improving healthcare performance. This study aimed to assess the validity of the Persian version of the Picker Patient Experience Questionnaire. Instrument & Methods: This descriptive cross-sectional study was condcted in Nikan Gharb and Nikan Aqdasiyeh hospitals in Tehran from April to May 2022. The Persian version of the Picker Patient Experience Questionnaire was prepared based on the translation-retranslation method. The face and content validity of the questionnaire was evaluated with the opinions of 10 experts. To check the tool validity, all patients discharged from the two hospitals were interviewed by phone from April 21 to May 21, 2022. The main dimensions and constructs of the questionnaire were determined by the exploratory factor analysis method. The questionnaire reliability was evaluated using the test-retest method by participation of 30 subjects. Findings: By checking the validity of the questionnaire, the items were included in 7 aspects which were in accordance with the main sections of the questionnaire (information and education, coordination of care, emotional support, respect for patient preferences, physical comfort, involvement of family and friends, and continuity and transition). The tool reliability for the 7 aspects by Cronbach's alpha was in the range of 0.744 to 0.911, and for the whole questionnaire was 0.804. Conclusion: The Persian version of Picker Patient Experience Questionnaire has the necessary validity to evaluate the experience of hospitalized patients in Iranian hospitals.

Purpose: The order-picking problem is important as one of the warehouse's logistics activities. This problem is defined as collecting orders from different warehouse locations to respond to customers' orders quickly. This paper aims to provide a multi-objective mathematical programming model for integrating the decisions of batching, routing, and scheduling of selectors with the packaging problem in a multi-warehouse environment. The objective functions include depreciation of the delivery times and total order picking costs.Methodology: In this research, first, by reviewing the literature in the field of order picking, the research gaps of the problem have been identified. Then, taking into account the main constraints of the problem, a multi-objective mathematical model has been formulated for the multi-warehouse order-picking problem. The classic Benders decomposition algorithm and the accelerated Benders decomposition algorithm have been used to solve the problem. The data related to the warehouses of a company producing sanitary products in Iran was used as a case study to validate the applicability of the proposed model, and its results were reported in the article.Findings: The proposed model's results indicate that CPLEX can solve these problems up to small sizes in an acceptable time. Also, the numerical results show the performance of the Benders decomposition algorithm and the accelerated Benders algorithm as suitable alternatives for solving the model in large-sized problems. The calculation results obtained from the implementation of the solution methods for the proposed model showed that in terms of the number of iterations and the calculation time, the accelerated Benders algorithm had better results than the classic Benders algorithm.Originality/Value: In this research, the order-picking problem with the integrity of operational decisions has been formulated as a multi-objective mathematical model for a multi-warehouse environment for the first time. Also, in this article regarding the solution method, exact solution approaches have been used for the first time considering the structure of the problem. The computation results show that the proposed algorithms are efficient and suitable methods for problem-solving.

Different types of contact, including contact between node pairs, any-contact of nodes, and contacts of the entire network, are used to characterize social relations in mobile social networks. Different modes of routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for nodes, improves the performance of these networks. However, there exists an important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in routing applications, it causes to use of the distribution of one type of contact for any mode of routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of routing. We propose a routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

Nowadays, the problem of garbage collection in Iran has become one of the serious phenomenon and problems in the form that it is manifested in all the cities and metropolises of the country. The problem of garbage collection possesses environmental, economic and social dimensions. The present study tries to narrate the life issues of garbage Pickers in Tehran using an interpretive approach. The theoretical view of the research is based on a critical approach and the use of Agamben's Homosacer concept. The research method is based on the fundamental qualitative method and the use of semi-structured interview and observation techniques. Thematic analysis is used to analyze the data. The findings of the research show that garbage Pickers face with many problems such as nutrition, sleep, addiction, etc. and they have unequal working relationships with contractors. Garbage Pickers are mostly men, immigrants, low-educated or illiterate and live in different places such as streets, worker accommodation centers, outskirts of cities and with their families. Garbage picking as a job is related to other social problems of the city like social inequalities urban consumption, child labor and black holes of urban waste. Urban garbage collectors, like other damaged and marginalized social groups, are the concept of urban homosuckers. Such people are not included in official support.

This paper considers the integrated order picking (joint order batching and Picker routing) and delivery problem in a manual Picker-to-parts and multi-block 3D warehouse with considering overbooking and delivery-delay allowed strategies. Received orders by the customers are grouped into the batches, assigned to the Pickers with horizontal and vertical velocities to compute the travel time, picked up from the shelves of the warehouse, and delivered to customers’ community. The warehouse’s policy is to accept orders for a certain number of unavailable products in addition to the available products. Thus, the concept of the overbooking strategy for supplying unavailable products and the delivery postponed strategy for delayed delivery is applied. Hence, this study introduces a novel mathematical model to deal with such a system, where the objective aims to minimize the cost of the completion time of all batches, the purchasing of the unavailable products and the return time of all vehicles to the depot. To solve this model, four new heuristic algorithms are devised, a broad range of numerical experiments is investigated to illustrate the validity and applicability of the proposed model and solution approaches.