Screening alternatives graphically by an extended case-based distance approach

Screening is a helpful process of multiple criteria decision aid (MCDA) to reduce a larger set of alternatives into a smaller one containing the best alternatives; thereby, decision makers are able to concentrate on evaluating alternatives within a smaller set. Therefore, determining how to assist decision makers in screening is an important issue for MCDA. This study proposes an extended case-based distance approach incorporating the advantages of a case-based distance method, a mixed-integer programming approach of discriminant analysis, and a multidimensional scaling technique to help decision makers screen alternatives visually in MCDA. The proposed approach can screen alternatives by evaluating sets of cases selected by decision makers, providing visual aids to observe decision context, reducing the number of misclassifications, and improving multiple solution problems. An interactive screening procedure is also developed to provide flexibility so that decision makers can check and adjust screening results iteratively.     

IMP: A decision aid for multiattribute evaluation using imprecise weight estimates

In multicriteria analysis, weights are inferred from judgements. Judgements are subject to uncertainty and the weights found depend on the method used so that weights must necessarily be imprecise. Describing weights by a suitable probability distribution captures this imprecision and leads to correspondingly imprecise estimates of the multiattribute scores given to alternatives. A method is described which enables the parameters of a Dirichlet distribution to be found from three point weight estimates and for this to be used to determine whether or not alternatives may justifiably be differentiated by their scores. A simple chart shows this information and permits easy interaction. An illustration shows the effects of different sources of imprecision and of aggregating individual assessments in a group.     

An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming

In this paper, we present an aggregate production planning (APP) model applied to a Portuguese firm that produces construction materials. A multiple criteria mixed integer linear programming (MCMILP) model is developed with the following performance criteria: (1) maximize profit, (2) minimize late orders, and (3) minimize work force level changes. It includes certain operational features such as partial inflexibility of the work force, legal restrictions on workload, work force size (workers to be hired and downsized), workers in training, and production and inventory capacity. The purpose is to determine the number of workers for each worker type, the number of overtime hours, the inventory level for each product category, and the level of subcontracting in order to meet the forecasted demand for a planning period of 12 months. Additionally, a decision support system (DSS) based on the MCMILP model is proposed. It will help practitioners find the “best” solution for an APP problem without having to familiarize themselves with the mathematical complexities associated with the model. An example to illustrate the use of the DSS is also included.     

Multicriteria decision support in local energy planning: An evaluation of alternative scenarios for the Sustainable Energy Action Plan

One of the major challenges for the implementation of local energy planning is the successful development of a Sustainable Energy Action Plan (SEAP) by the local authorities (especially within the framework of their participation to the Covenant of Mayors’ initiative). This aspect constitutes a decision making problem, since the local authorities have to identify the best fields of actions and opportunities for reaching their long-term CO₂ reduction target. However, the already available methods and tools do not offer an integrated framework for the SEAPs’ development and especially the selection of sustainable Renewable Energy Sources (RES) and Rational Use of Energy (RUE) technologies. In this context, the aim of this paper is to present a participatory supportive framework for the implementation of local energy planning. At the first level, the proposed approach incorporates the development of alternative Scenarios of Actions (using knowledge-based process, participatory approach and aspiration level). At the second level, a direct and transparent multicriteria decision support is introduced, in order to evaluate the feasible Scenarios. It includes the application of a multicriteria ordinal regression approach and an extreme ranking analysis method for the estimation of the best and worst possible ranking position of each Scenario. The results from the pilot appraisal of the methodological approach to a “real” problem are presented and discussed. The adopted approach contributes to the selection of the most appropriate combination of RES/RUE actions, supporting in this way the local authorities to the development of their SEAP.     

A decision support system for modelling and implementing the supply network configuration and operations scheduling problem in the machine tool industry

This paper presents a decision support system to simultaneously solve the supply network configuration problem and the operations scheduling problem for the machine tool industry. A novel database structure, which is able to consider alternative operations and alternative bills of material, has been used. An algorithm for complete enumeration to determine all the feasible solutions using stroke graphs is introduced. A multiagent-based simulator evaluates the different key performance indicators that the supply network deals with for each alternative solution (e.g. workload, profits, delivery times, etc.) to determine that ‘satisficed’ by the collaborative decision-making among its members. A case study based on a Spanish company that assembles highly customised machines and tools in several European plants is considered. From the experiments results based on data linked to this industry, it will be demonstrated that the tool is potentially useful for stakeholders and for the central decision-maker to make decisions collaboratively in a multisite context case.     

Power planning in ICT infrastructure: A multi-criteria operational performance evaluation approach

It is critical for information and communications technology (ICT) companies to carry our effective power planning, in order to support the growing number of services they provide, and this traditionally relies on the tacit knowledge and experience of senior staff. The loss of such domain knowledge resulting from the retirement of staff is an important issue for organizations such as Chunghwa Telecom (CHT), the largest ICT operator in Taiwan. This study thus develops a systematic power planning model using a multi-criteria operational performance evaluation. A group version of the fuzzy repertory grid and fuzzy TOPSIS approaches is applied to elicit a set of evaluation criteria that senior staff agree on, and then the priorities of the telecom rooms are evaluated against this. In addition, a new factor, reflecting the attitudes of the decision makers with respect to the degree of strictness, is defined to determine the superiority and inferiority of each alternative compared to the others. Furthermore, a novel decision aggregation strategy regarding the degree of variation among decision makers is proposed, and a quantitative assessment is carried out to analyze its impact on the ranking results in an objective manner. The proposed model may help ICT organizations to more effectively manage their power resources, and thus obtain competitive advantages.     

Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain

The food sector has a prodigious focus and is constantly gaining in importance in today’s global economic marketplace. Due to an increasing global population, society faces a greater challenge for sustainable food production, quality, distribution, and food safety in the food supply chain. Adopting green supply chain management (GSCM) elements is essential for utilizing the food supply chain in an environmentally benign way. As a solution to the above challenge, the economic and green characteristics for supplier selection in green purchasing are studied in this paper. For an organization, the evaluation and selection of the green supplier is a vital issue due to several tangible and intangible criteria involved. Accordingly, we apply multiple criteria decision aiding techniques.We propose a hybrid approach that combines the revised Simos procedure, PROMETHEE methods, algorithms for constructing a group compromise ranking, and robustness analysis. At first, the revised Simos procedure is used to derive the criteria weights. Next, the PROMETHEE method is applied to rank the suppliers according to each Decision Maker׳s (DM׳s) preferences. Then, the compromise ranking is constructed to minimize the distance of the individual׳s rankings from the solution adopted by the whole group. For this purpose, we introduce and apply some original procedures based on Binary Linear Programming. Finally, the results are validated against the outcomes of robustness analysis. The applicability and efficiency of the proposed approach is endorsed with a case study in an Indian food industry.     

供应链物流运作能力计划模型与分析

考察了某种产品供应链系统的一次性物流运作过程,建立了这个系统的物流能力动态规划模型。针对供应链中物流运作能力的流通量指标进行了较为深入的理论分析,探讨了使得系统成本最小化的最优物流能力及系统各阶段需配置的流通量。最优物流能力策略体现为两个关键量,即下界和上界。如果可得输入量小于下界则选择不开展物流;如果可得输入超出了下界,物流能力可以足够大但不超过上界。运用数学归纳法对优化结果进行了证明,并结合算例检验了模型的效果。