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In this chapter, we consider the model of call center incoming call forecasting and staffing-level optimization. We first present the structure of the model and how an agent-based modeling technique could enrich the decision rule and the model. A matrix layout is introduced to present the model so that it can be understood in an efficient way from the perspective of a programmer. The agent-based queuing model will be used in forecasting. We then utilize the bisection method and stepwise method to optimize the staff level to satisfy a target range service-level criteria. Call center management could use the model in practice for their management forecasting and optimization decision-making process in terms of how many agents they need to achieve the target business efficiency goal.

The role of information technology is very important, especially in achieving related performance to optimize supply chain management as recognized by various findings literature. The existence of computer equipment is no longer sufficient to cope with the various industry issues, especially those requiring the latest information from the aspect of visibility and information accuracy. This study focuses on the importance of visibility and accuracy of the information on the coffee supply chain and aims to identify the use of information technology to eliminate problems in the coffee industry, especially in West Java. The study begins by compiling basic assumptions and rules of thought used in research, data collection, data reduction, categorization, analysis, interpretation, and data display, and the conclusion. The data analysis used a decision-making trial and evaluation laboratory (DEMATEL), which was used to determine the representation of critical factors contained in the research dimensions. As a finding the coffee supply chain in West Java has not been responsive and efficient yet, so improvements need to be made to get high added value for regional economic growth. The results of the study also identified several obstacles along the supply chain and solution based on a high level of information accuracy with several challenges to utilize it, namely (1) data and information sharing, (2) forecasting optimization, and (3) collaborative planning. As a suggestion to increase visibility in supply chain management, further research is needed to create relevant software and systems to trace the solutions to the causes and challenges faced to improve the accuracy of the information and its visibility.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.