This study, both descriptive and exploratory, aims to examine the scientific literature on the supply chain performance measurement (SCPM) in the automotive sector over the last 12 years. The analysis featured 30 articles corresponding to the research topic of the Scopus database. The most pertinent articles, authors, keywords, countries, research laboratories and journals are presented using the analysis of bibliographies on the subject from 2007 to 2018 in the Industrial Engineering domain. The conclusion is performed by the systematic analysis that the automotive sector is well controlled on the subject of performance. The selected studies show that lack of understanding of the performance measurement system (PMS) and lack of management dedication are the main obstacles. Finally, various guidelines are provided to optimize the supply chain in the automotive sector.

The proposed work presents the design and application of many-objective Jaya (MaOJaya) algorithm to optimize many-objective benchmark optimization problems. The basic Jaya algorithm is modified by introducing non-dominated sorting and tournament selection scheme of NSGA-II. The reference point mechanism is introduced to traverse algorithm towards the best solutions. The basic Jaya algorithm is modified while preserving its essential properties. The Tchebycheff – a decomposition based approach is used to simplify the complex MaOPs. The proposed MaOJaya algorithm is tested on DTLZ benchmark functions with objectives ranging from three to ten to measure its applicability and effectiveness to solve many-objective optimization problems. The IGD and Hypervolume performance metrics are used to evaluate the performance of proposed MaOJaya algorithm. The obtained IGD and Hypervolume values compared with the best known results and it is observed that, the proposed MaOJaya algorithm gives competitive or better results than known best results.

Scheduling and layout planning are two important areas of operations research, which are used in the areas of production planning, logistics and supply chain management. In many industries locations of machines are not specified, previously, therefore, it is necessary to consider both location and scheduling, simultaneously. This paper presents a mathematical model to consider both scheduling and layout planning for parallel machines in discrete and continuous spaces, concurrently. The preliminary results have indicated that the integrated model is capable of handling problems more efficiently.

We present here a hybrid algorithm for the Flexible Job-Shop Scheduling Problem (FJSSP). This problem involves the optimal use of resources in a flexible production environment in which each operation can be carried out by more than a single machine. Our algorithm allocates, in a first step, the machines to operations and in a second stage it sequences them by integrating a Multi-Objective Evolutionary Algorithm (MOEA) and a path-dependent search algorithm (Multi-Objective Simulated Annealing), which is enacted at the genetic phase of the procedure. The joint interaction of those two components yields a very efficient procedure for solving the FJSSP. An important step in the development of the algorithm was the selection of the right MOEA. Candidates were tested on problems of low, medium and high complexity. Further analyses showed the relevance of the search algorithm in the hybrid structure. Finally, comparisons with other algorithms in the literature indicate that the performance of our alternative is good.

The purpose of this study is to examine the relationship between zakat collection and distribution as core supply chain perspective for their economic impact in the region of Indonesia. The study collects the necessary data from various respondents who are paying zakat and interacting with various collections and distribution centers of zakat. A sample of 362 respondents is finally observed for descriptive, correlational and regression analysis. It is observed that both collection and distribution of zakat are core indicators in terms of supply chain with their economic outcomes. More specifically, zakat collection and distribution have positive impacts on equal distribution of wealth, cleanliness of wealth, economic growth, provision of educational facilities to needy students, and delivery of good health facilities in Indonesia. In addition, it is also found that more collection and distribution centers can lead to better economic output in the economy, where the role of mosques and Muslim community center is very important. Besides, some limitations in the current research need to be readdressed in future. First, the study has provided a limited context of zakat collection and distribution which could be expanded while adding the latest policies being adopted by the local government and their economic impact. Second, future studies could be reconsidered through getting the significant responses from those who are directly linked to the collection and distribution of zakat as they have much more body of knowledge about their economic implications.

This paper tackles an extension to the Multi-activity Combined Timetabling and Crew Scheduling Problem (MCTCSP). The goal of the original problem is to schedule the minimum number of homogenous workers required, in order to visit a set of customers characterized by services needed against schedule availability. However, since in home services it is common to have specialized workers, a mathematical model considering a heterogeneous workforce is proposed. As a solution, a GRASP-based algorithm is designed. In order to test the metaheuristic performance, 110 instances from the literature are adapted to include categorical skills. In addition, another 10 instances are randomly generated to consider large problems. The results show that the proposed GRASP finds optimal solutions in 46% of the cases and saves 40–96% computational time.

In today’s world, due to rapid changes in the market, scheduling as one of the most fundamental issues of competitive production, plays a very important role in maintaining the competitive position and survival of manufacturing organizations, therefore, development of scheduling models in order to improve the timing criteria is of great importance. In this research, we put the development of a no-wait flow-shop scheduling model alongside with the effect of learning into consideration to minimize the cost of consumption of resources. Finding the correct sequence of two machines’ performance and optimized allocation of the resources for any performance on each machine, were considered as the main goal in this study. To solve the problem, metaheuristic genetic algorithms, particle swarm optimization, imperialist competitive algorithms, optimization of the whale and the League Champions algorithms, have been used. The statistical comparisons and also using of TOPSIS Multi-Criteria Decision Making method, indicate high level of efficiency of the League Champions algorithm with the utility weight of 0.9516.

This paper presents a mathematical model for scheduling of a single machine when there are preemptions in jobs. The primary objective of the study is to minimize different objectives such as earliness, tardiness and work in process. The proposed mathematical problem is considered as NP-Hard and the optimal solution is available for small scale problems. Therefore, a genetic algorithm (GA) is developed to solve the problem for large-scale problems. The implementation of the proposed model is compared with GA for problems with up to 50 jobs using three methods of roulette wheel sampling, random sampling and competition sampling. The results have indicated that competition sampling has reached optimal solutions for small scale problems and it could obtain better near-optimal solutions in relatively lower running time compared with other sampling methods.

In recent years, logistics development is considered as an important aspect of any country’s development. Outsourcing logistics activities to third party logistics (3PL) providers is a common way to achieve logistics development. On the other hand, globalization and increasing customers’ concern about the environmental impact of activities as well as the appearance of the issue of social responsibility have led companies employ sustainable supply chain management, which considers economic, environmental and social benefits, simultaneously. This paper proposes a multi-objective model to design logistics network for 3PL providers by considering sustainable objectives under uncertainty. Objective functions include minimizing the total cost, minimizing greenhouse gas emission and maximizing social responsibility subject to fair access to products, number of created job opportunities and local community development. It is worth mentioning that in the present paper the perishability of products is also considered. A numerical example is provided to solve and validate model using augmented Epsilon-Constraint method. The results show that three sustainable objectives were in conflict and as the one receives more desirable values, the others fall into more undesirable values. In addition, by increasing maximum perishable time periods and by considering lateral transshipment among facilities of a level one can improve sustainability indices of the problem, which indicates the necessity of such policy in improving network sustainability.

Employees’ knowledge sharing and innovative work behavior play an important role for the development of Vietnam telecommunication enterprises. Knowledge sharing along with two central processes; namely knowledge donation and collection, fosters employees’ innovative work behavior of Vietnam telecommunication enterprises. Based on a sample size survey of 396 Vietnam telecommunication employees and exploration factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM), the study determines factors such as trust, enjoyment in helping others, knowledge self-efficacy, management support, using information and communication technology significantly influence knowledge donation and collection. At the same time, knowledge donation and collection have positive impacts on employees’ innovative work behavior of Vietnam telecommunication enterprises. Finally, several suggestions for enhancing employees’ knowledge sharing and innovative work behavior of Vietnam telecommunication enterprises managers are given.